From 5e634b8e025eade30d4055fcc0bc2b5ef6d29dc4 Mon Sep 17 00:00:00 2001
From: lazappi <lazappi@users.noreply.github.com>
Date: Wed, 8 Nov 2023 09:26:31 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20lazappi/?=
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 =?UTF-8?q?=F0=9F=9A=80?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 404.html                                      |   2 +-
 LICENSE-text.html                             |   2 +-
 apple-touch-icon-120x120.png                  | Bin 12571 -> 12571 bytes
 apple-touch-icon-60x60.png                    | Bin 5021 -> 5021 bytes
 apple-touch-icon-76x76.png                    | Bin 6796 -> 6796 bytes
 apple-touch-icon.png                          | Bin 12571 -> 12571 bytes
 articles/clustree.html                        |  29 +++++++++++++-----
 .../figure-html/nba-overlay-labels-1.png      | Bin 104169 -> 104345 bytes
 .../figure-html/nba-overlay-sides-1.png       | Bin 102161 -> 101923 bytes
 .../figure-html/nba-overlay-sides-2.png       | Bin 98124 -> 98700 bytes
 .../figure-html/plot-gene-1.png               | Bin 84449 -> 82795 bytes
 .../figure-html/seurat-plot-1.png             | Bin 81498 -> 83032 bytes
 articles/index.html                           |   2 +-
 authors.html                                  |   2 +-
 favicon-16x16.png                             | Bin 1298 -> 1298 bytes
 favicon-32x32.png                             | Bin 2433 -> 2433 bytes
 index.html                                    |   2 +-
 news/index.html                               |   4 +--
 pkgdown.yml                                   |   2 +-
 reference/add_node_labels.html                |   2 +-
 reference/add_node_points.html                |   2 +-
 reference/aggr_metadata.html                  |   2 +-
 reference/assert_colour_node_aes.html         |   2 +-
 reference/assert_node_aes.html                |   2 +-
 reference/assert_numeric_node_aes.html        |   2 +-
 reference/build_tree_graph.html               |   2 +-
 reference/calc_sc3_stability.html             |   2 +-
 reference/calc_sc3_stability_cluster.html     |   2 +-
 reference/check_node_aes_list.html            |   2 +-
 reference/clustree-package.html               |   2 +-
 reference/clustree.html                       |   2 +-
 reference/clustree_overlay.html               |   2 +-
 reference/get_tree_edges.html                 |   2 +-
 reference/get_tree_nodes.html                 |   2 +-
 reference/index.html                          |   2 +-
 reference/nba_clusts.html                     |   2 +-
 reference/overlay_node_points.html            |   2 +-
 reference/plot_overlay_side.html              |   2 +-
 reference/sc_example.html                     |   2 +-
 reference/store_node_aes.html                 |   2 +-
 search.json                                   |   2 +-
 41 files changed, 51 insertions(+), 38 deletions(-)

diff --git a/404.html b/404.html
index fbfe3a7..ccb524b 100644
--- a/404.html
+++ b/404.html
@@ -37,7 +37,7 @@
     
     <a class="navbar-brand me-2" href="https://lazappi.github.io/clustree/index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/LICENSE-text.html b/LICENSE-text.html
index 04d37bf..d8c126b 100644
--- a/LICENSE-text.html
+++ b/LICENSE-text.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/apple-touch-icon-120x120.png b/apple-touch-icon-120x120.png
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delta 69
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diff --git a/apple-touch-icon.png b/apple-touch-icon.png
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GIT binary patch
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delta 69
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diff --git a/articles/clustree.html b/articles/clustree.html
index 0157d3b..7d29542 100644
--- a/articles/clustree.html
+++ b/articles/clustree.html
@@ -39,7 +39,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -346,11 +346,6 @@ <h3 id="singlecellexperiment-objects">
 <h3 id="seurat-objects">
 <code>Seurat</code> objects<a class="anchor" aria-label="anchor" href="#seurat-objects"></a>
 </h3>
-<blockquote>
-<p><strong>NOTE:</strong> This section requires the Seurat package
-(&gt;= 5.0.0). This package isn’t installed so the results won’t be
-shown.</p>
-</blockquote>
 <p>Clustering trees can also be produced directly from
 <code>Seurat</code> objects. Let’s convert our
 <code>SingleCellExperiment</code> to <code>Seurat</code> format:</p>
@@ -364,18 +359,35 @@ <h3 id="seurat-objects">
 <span></span>
 <span><span class="co"># Add the t-SNE embedding</span></span>
 <span><span class="va">seurat</span><span class="op">[[</span><span class="st">'TSNE'</span><span class="op">]</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/CreateDimReducObject.html" class="external-link">CreateDimReducObject</a></span><span class="op">(</span>embeddings <span class="op">=</span> <span class="va">sc_example</span><span class="op">$</span><span class="va">tsne</span>,</span>
-<span>                                         key <span class="op">=</span> <span class="st">"tSNE_"</span><span class="op">)</span></span></code></pre></div>
+<span>                                         key <span class="op">=</span> <span class="st">"tSNE_"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; Warning: No assay specified, setting assay as RNA by default.</span></span>
+<span><span class="co">#&gt; Warning: No columnames present in cell embeddings, setting to 'tSNE_1:2'</span></span></code></pre></div>
 <p>In this case the clustering information is held in the
 <code>meta.data</code> slot which can be accessed using the
 <code>[[</code> operator:</p>
 <div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">seurat</span><span class="op">[[</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div>
+<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">seurat</span><span class="op">[[</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span>
+<span><span class="co">#&gt;          orig.ident nCount_RNA nFeature_RNA nGene nUMI res.0 res.0.1 res.0.2</span></span>
+<span><span class="co">#&gt; Cell1 SeuratProject       4458          503   503 4458     0       0       0</span></span>
+<span><span class="co">#&gt; Cell2 SeuratProject       4722          549   549 4722     0       0       0</span></span>
+<span><span class="co">#&gt; Cell3 SeuratProject       3960          504   504 3960     0       0       0</span></span>
+<span><span class="co">#&gt; Cell4 SeuratProject       4822          525   525 4822     0       0       0</span></span>
+<span><span class="co">#&gt; Cell5 SeuratProject       4058          492   492 4058     0       0       0</span></span>
+<span><span class="co">#&gt; Cell6 SeuratProject       6780          610   610 6780     0       0       0</span></span>
+<span><span class="co">#&gt;       res.0.3 res.0.4 res.0.5 res.0.6 res.0.7 res.0.8 res.0.9 res.1</span></span>
+<span><span class="co">#&gt; Cell1       1       1       1       1       0       0       0     0</span></span>
+<span><span class="co">#&gt; Cell2       1       1       1       1       0       0       0     0</span></span>
+<span><span class="co">#&gt; Cell3       0       0       0       0       1       1       1     1</span></span>
+<span><span class="co">#&gt; Cell4       0       0       0       0       1       1       1     1</span></span>
+<span><span class="co">#&gt; Cell5       1       1       1       1       0       0       0     0</span></span>
+<span><span class="co">#&gt; Cell6       0       0       0       0       1       1       1     1</span></span></code></pre></div>
 <p>We can now produce a clustering tree using this object. In this
 example the prefix for clustering columns is <code>res.</code> but in
 most cases the default prefix from <code>Seurat</code> will be
 automatically used.</p>
 <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/clustree.html">clustree</a></span><span class="op">(</span><span class="va">seurat</span>, prefix <span class="op">=</span> <span class="st">"res."</span><span class="op">)</span></span></code></pre></div>
+<p><img src="clustree_files/figure-html/seurat-plot-1.png" width="700"></p>
 <blockquote>
 <p>Note: This example uses the newer Seurat object available in version
 3.0.0 or greater of Seurat. There is also an interface for the older
@@ -392,6 +404,7 @@ <h3 id="using-genes-as-aesthetics">Using genes as aesthetics<a class="anchor" ar
 <div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/clustree.html">clustree</a></span><span class="op">(</span><span class="va">seurat</span>, prefix <span class="op">=</span> <span class="st">"res."</span>,</span>
 <span>         node_colour <span class="op">=</span> <span class="st">"Gene730"</span>, node_colour_aggr <span class="op">=</span> <span class="st">"median"</span><span class="op">)</span></span></code></pre></div>
+<p><img src="clustree_files/figure-html/plot-gene-1.png" width="700"></p>
 </div>
 </div>
 <div class="section level2">
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GIT binary patch
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diff --git a/index.html b/index.html
index 8034a11..91b8fd6 100644
--- a/index.html
+++ b/index.html
@@ -47,7 +47,7 @@
     
     <a class="navbar-brand me-2" href="index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/news/index.html b/news/index.html
index ddd16bc..08f996f 100644
--- a/news/index.html
+++ b/news/index.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -55,7 +55,7 @@
 
     <div class="section level2">
 <h2 class="pkg-version" data-toc-text="0.5.1" id="clustree-051-2023-11-05">
-<em>clustree</em> 0.5.1 (2023-11-05)<a class="anchor" aria-label="anchor" href="#clustree-051-2023-11-05"></a></h2>
+<em>clustree</em> 0.5.1 (2023-11-05)<a class="anchor" aria-label="anchor" href="#clustree-051-2023-11-05"></a></h2><p class="text-muted">CRAN release: 2023-11-05</p>
 <ul><li>Minor updates for compatibility with <em>Seurat</em> &gt;= 5.0.0 and <em>ggplot2</em> &gt;= 3.4.0</li>
 </ul><div class="section level3">
 <h3 id="development-versions-0-5-1">Development versions<a class="anchor" aria-label="anchor" href="#development-versions-0-5-1"></a></h3>
diff --git a/pkgdown.yml b/pkgdown.yml
index bf9615c..485a580 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -3,7 +3,7 @@ pkgdown: 2.0.7
 pkgdown_sha: ~
 articles:
   clustree: clustree.html
-last_built: 2023-11-05T18:41Z
+last_built: 2023-11-08T09:25Z
 urls:
   reference: https://lazappi.github.io/clustree/reference
   article: https://lazappi.github.io/clustree/articles
diff --git a/reference/add_node_labels.html b/reference/add_node_labels.html
index 012fdc7..c8f3f97 100644
--- a/reference/add_node_labels.html
+++ b/reference/add_node_labels.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/add_node_points.html b/reference/add_node_points.html
index b6241f0..bc76fdd 100644
--- a/reference/add_node_points.html
+++ b/reference/add_node_points.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/aggr_metadata.html b/reference/aggr_metadata.html
index a01f670..414ecb1 100644
--- a/reference/aggr_metadata.html
+++ b/reference/aggr_metadata.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/assert_colour_node_aes.html b/reference/assert_colour_node_aes.html
index 8a97e19..2fa316a 100644
--- a/reference/assert_colour_node_aes.html
+++ b/reference/assert_colour_node_aes.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/assert_node_aes.html b/reference/assert_node_aes.html
index f87157a..4fa827a 100644
--- a/reference/assert_node_aes.html
+++ b/reference/assert_node_aes.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/assert_numeric_node_aes.html b/reference/assert_numeric_node_aes.html
index d07700f..b13370b 100644
--- a/reference/assert_numeric_node_aes.html
+++ b/reference/assert_numeric_node_aes.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/build_tree_graph.html b/reference/build_tree_graph.html
index f5f63fc..d557284 100644
--- a/reference/build_tree_graph.html
+++ b/reference/build_tree_graph.html
@@ -18,7 +18,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/calc_sc3_stability.html b/reference/calc_sc3_stability.html
index 604f2ec..553dfee 100644
--- a/reference/calc_sc3_stability.html
+++ b/reference/calc_sc3_stability.html
@@ -22,7 +22,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/calc_sc3_stability_cluster.html b/reference/calc_sc3_stability_cluster.html
index b2a3dca..ed63f7c 100644
--- a/reference/calc_sc3_stability_cluster.html
+++ b/reference/calc_sc3_stability_cluster.html
@@ -20,7 +20,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/check_node_aes_list.html b/reference/check_node_aes_list.html
index ffdf0e6..324fba3 100644
--- a/reference/check_node_aes_list.html
+++ b/reference/check_node_aes_list.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/clustree-package.html b/reference/clustree-package.html
index 46fe5b3..4a13907 100644
--- a/reference/clustree-package.html
+++ b/reference/clustree-package.html
@@ -24,7 +24,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/clustree.html b/reference/clustree.html
index e217b7f..d8b472a 100644
--- a/reference/clustree.html
+++ b/reference/clustree.html
@@ -18,7 +18,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/clustree_overlay.html b/reference/clustree_overlay.html
index 64f2f03..008f5f8 100644
--- a/reference/clustree_overlay.html
+++ b/reference/clustree_overlay.html
@@ -18,7 +18,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/get_tree_edges.html b/reference/get_tree_edges.html
index c55bb97..0305d8d 100644
--- a/reference/get_tree_edges.html
+++ b/reference/get_tree_edges.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/get_tree_nodes.html b/reference/get_tree_nodes.html
index adfeea6..12d29df 100644
--- a/reference/get_tree_nodes.html
+++ b/reference/get_tree_nodes.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/index.html b/reference/index.html
index 2f8131a..575d9cc 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/nba_clusts.html b/reference/nba_clusts.html
index 8dbf03a..b83763e 100644
--- a/reference/nba_clusts.html
+++ b/reference/nba_clusts.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/overlay_node_points.html b/reference/overlay_node_points.html
index 8537c19..faa8d3a 100644
--- a/reference/overlay_node_points.html
+++ b/reference/overlay_node_points.html
@@ -18,7 +18,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/plot_overlay_side.html b/reference/plot_overlay_side.html
index 5124e9b..681728b 100644
--- a/reference/plot_overlay_side.html
+++ b/reference/plot_overlay_side.html
@@ -20,7 +20,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/sc_example.html b/reference/sc_example.html
index ba5f17b..f9f061d 100644
--- a/reference/sc_example.html
+++ b/reference/sc_example.html
@@ -18,7 +18,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/store_node_aes.html b/reference/store_node_aes.html
index a4a0089..f754a78 100644
--- a/reference/store_node_aes.html
+++ b/reference/store_node_aes.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">clustree</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.0.9001</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/search.json b/search.json
index 241cb19..1773f8a 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"what-is-a-clustering-tree","dir":"Articles","previous_headings":"","what":"What is a clustering tree?","title":"Plotting clustering trees","text":"Clustering analysis used many contexts group similar samples. One problem conducting kind analysis many clusters use. usually controlled parameter provided clustering algorithm, \\(k\\) \\(k\\)-means clustering. Statistics designed help make choice typically either compare two clusterings score single clustering. clustering tree different visualises relationships range resolutions. build clustering tree need look cells move clustering resolution increased. cluster forms node tree edges constructed considering cells cluster lower resolution (say \\(k = 2\\)) end cluster next highest resolution (say \\(k = 3\\)). connecting clusters way can see clusters related , clearly distinct unstable. Extra information cells node can also overlaid order help make decision resolution use. information clustering trees please refer associated publication (Zappia Oshlack 2018).","code":""},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"a-simple-example","dir":"Articles","previous_headings":"","what":"A simple example","title":"Plotting clustering trees","text":"demonstrate clustering tree looks like work short example using nba_clusts dataset.","code":""},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"the-data","dir":"Articles","previous_headings":"A simple example","what":"The data","title":"Plotting clustering trees","text":"nba_clusts dataset consists basic statistics 150 NBA players 2017, 50 three positions (Center, Point Guard Shooting Guards). dataset clustered using \\(k\\)-means different values \\(k\\). information see ?nba_clusts. Let’s load data take look: data.frame player positions statistics (turnover percentage, rebound percentage, assist percentage field goal percentage) well additional columns. columns contain cluster assignments clustering data using \\(k\\)-means values \\(k\\) \\(k = 1\\) \\(k = 5\\).","code":"library(clustree) #> Loading required package: ggraph #> Loading required package: ggplot2 data(\"nba_clusts\")  head(nba_clusts) #>   Position TurnoverPct ReboundPct AssistPct FieldGoalPct K1 K2 K3 K4 K5 #> 1   Center        10.6       17.4      14.7         50.2  1  2  2  1  2 #> 2   Center         9.6       19.6      16.9         46.8  1  2  2  1  2 #> 3   Center        16.0       14.2       5.4         57.1  1  2  2  1  2 #> 4   Center        17.2       14.9       2.7         58.3  1  2  2  1  2 #> 5   Center        11.7       20.8       4.4         55.7  1  2  2  1  2 #> 6   Center        12.5       17.4       7.9         54.5  1  2  2  1  2 #>          PC1       PC2 #> 1  -5.907675 -4.559588 #> 2  -3.398585 -4.015772 #> 3 -14.705825 -3.907384 #> 4 -17.489016 -3.598523 #> 5 -17.705077 -3.455650 #> 6 -13.069032 -3.845442"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"plotting-a-tree","dir":"Articles","previous_headings":"A simple example","what":"Plotting a tree","title":"Plotting clustering trees","text":"clustering information need build clustering tree. column must consist numeric values indicating cluster sample assigned . plot tree just pass information clustree function. also need specify prefix string indicate columns contain clusterings.  can see one cluster distinct change value \\(k\\). Center players different positions. side tree see single cluster splits two clusters expect see. tree becomes messier node multiple incoming edges. good indication clustered data.","code":"clustree(nba_clusts, prefix = \"K\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"controlling-aesthetics","dir":"Articles","previous_headings":"A simple example","what":"Controlling aesthetics","title":"Plotting clustering trees","text":"default size node related number samples cluster colour indicates clustering resolution. Edges coloured according number samples represent transparency shows incoming node proportion, number samples edge divided number samples node points . can control aesthetics setting specific values:  can also link aesthetics information samples. additional columns dataset available added attributes nodes tree. node represents multiple samples need supply aggregation function use well specifying column name. Let’s try colouring nodes according rebound percentage:  can clearly see distinct cluster containing Center players higher rebound percentage average compared clusters.","code":"clustree(nba_clusts, prefix = \"K\", node_colour = \"purple\", node_size = 10,          node_alpha = 0.8) clustree(nba_clusts, prefix = \"K\", node_colour = \"ReboundPct\",          node_colour_aggr = \"mean\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"sc3-stability-index","dir":"Articles","previous_headings":"A simple example > Controlling aesthetics","what":"SC3 stability index","title":"Plotting clustering trees","text":"Apart information dataset can useful display measures clustering quality aesthetics. stability index {SC3} package (Kiselev et al. 2017) measures stability clusters across resolutions automatically calculated clustering tree built. can accessed setting aesthetic \"sc3_stability\" calculated cluster don’t need provide aggregation function. example:","code":"clustree(nba_clusts, prefix = \"K\", node_colour = \"sc3_stability\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"layout","dir":"Articles","previous_headings":"A simple example","what":"Layout","title":"Plotting clustering trees","text":"default tree drawn using Reingold-Tilford tree layout algorithm tries place nodes parents (Reingold Tilford 1981). Alternatively use Sugiyama layout specifying layout argument. algorithm tries minimise number crossing edges (Sugiyama, Tagawa, Toda 1981) can produce attractive trees cases.  layout algorithms clustree() uses slightly modified versions tree default. core network edges, highest -proportion edge node, used creating layout. cases leads attractive trees easier interpret. turn , use edges deciding layout, can set use_core_edges FALSE.","code":"clustree(nba_clusts, prefix = \"K\", layout = \"sugiyama\") clustree(nba_clusts, prefix = \"K\", layout = \"sugiyama\", use_core_edges = FALSE)"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"adding-labels","dir":"Articles","previous_headings":"A simple example","what":"Adding labels","title":"Plotting clustering trees","text":"make easy identify clusters cluster nodes labelled cluster number (controlled using node_text arguments) sometimes useful add labels additional information. done way aesthetics. label nodes maximum assist percentage:  One way can useful assigned labels samples. custom function labels cluster players position, otherwise labels cluster “mixed”:","code":"clustree(nba_clusts, prefix = \"K\", node_label = \"AssistPct\",          node_label_aggr = \"max\") label_position <- function(labels) {     if (length(unique(labels)) == 1) {         position <- as.character(unique(labels))     } else {         position <- \"mixed\"     }     return(position) }  clustree(nba_clusts, prefix = \"K\", node_label = \"Position\",          node_label_aggr = \"label_position\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"clustering-trees-for-scrna-seq-data","dir":"Articles","previous_headings":"","what":"Clustering trees for scRNA-seq data","title":"Plotting clustering trees","text":"Clustering become core tool analysing single-cell RNA-sequencing (scRNA-seq) datasets. datasets contain gene expression measurements hundreds hundreds thousands cells. Often samples come complex tissues containing many types cells clustering used group similar cells together. make easier produce clustering trees kinds datasets provide interfaces objects commonly used analyse scRNA-seq data. clustree package contains example simulated scRNA-seq data clustered using {SC3} {Seurat} (Satija et al. 2015) packages.","code":"data(\"sc_example\") names(sc_example) #> [1] \"counts\"          \"logcounts\"       \"tsne\"            \"sc3_clusters\"    #> [5] \"seurat_clusters\""},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"singlecellexperiment-objects","dir":"Articles","previous_headings":"Clustering trees for scRNA-seq data","what":"SingleCellExperiment objects","title":"Plotting clustering trees","text":"SingleCellExperiment one common objects, used across range Bioconductor packages. Let’s look example, first need convert example dataset SingleCellExperiment object: clustering information held coldata slot. can plot clustering tree way data.frame. case clustering column names contain suffix needs stripped away, pass along well.","code":"#> Warning: replacing previous import 'S4Arrays::makeNindexFromArrayViewport' by #> 'DelayedArray::makeNindexFromArrayViewport' when loading 'SummarizedExperiment' suppressPackageStartupMessages(library(\"SingleCellExperiment\"))  sce <- SingleCellExperiment(assays = list(counts = sc_example$counts,                                           logcounts = sc_example$logcounts),                             colData = sc_example$sc3_clusters,                             reducedDims = SimpleList(TSNE = sc_example$tsne)) head(colData(sce)) #> DataFrame with 6 rows and 8 columns #>       sc3_1_clusters sc3_2_clusters sc3_3_clusters sc3_4_clusters #>             <factor>       <factor>       <factor>       <factor> #> Cell1              1              2              3              4 #> Cell2              1              2              3              2 #> Cell3              1              1              1              1 #> Cell4              1              1              1              3 #> Cell5              1              2              3              4 #> Cell6              1              2              2              2 #>       sc3_5_clusters sc3_6_clusters sc3_7_clusters sc3_8_clusters #>             <factor>       <factor>       <factor>       <factor> #> Cell1              3              2              2              3 #> Cell2              2              1              1              1 #> Cell3              5              4              4              5 #> Cell4              4              3              3              4 #> Cell5              3              2              5              8 #> Cell6              2              1              1              1 clustree(sce, prefix = \"sc3_\", suffix = \"_clusters\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"seurat-objects","dir":"Articles","previous_headings":"Clustering trees for scRNA-seq data","what":"Seurat objects","title":"Plotting clustering trees","text":"NOTE: section requires Seurat package (>= 5.0.0). package isn’t installed results won’t shown. Clustering trees can also produced directly Seurat objects. Let’s convert SingleCellExperiment Seurat format: case clustering information held meta.data slot can accessed using [[ operator: can now produce clustering tree using object. example prefix clustering columns res. cases default prefix Seurat automatically used. Note: example uses newer Seurat object available version 3.0.0 greater Seurat. also interface older seurat object may deprecated future.","code":"suppressPackageStartupMessages(library(\"Seurat\"))  # Create the Seurat object, Seurat >= expects a sparse matrix seurat <- CreateSeuratObject(counts = as(sc_example$counts, \"sparseMatrix\"),                              data = as(sc_example$logcounts, \"sparseMatrix\"),                              meta.data = sc_example$seurat_clusters)  # Add the t-SNE embedding seurat[['TSNE']] <- CreateDimReducObject(embeddings = sc_example$tsne,                                          key = \"tSNE_\") head(seurat[[]]) clustree(seurat, prefix = \"res.\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"using-genes-as-aesthetics","dir":"Articles","previous_headings":"Clustering trees for scRNA-seq data","what":"Using genes as aesthetics","title":"Plotting clustering trees","text":"well able use additional columns aesthetics can also use expression individual genes. Let’s colour nodes Seurat tree Gene730 (highly variable gene). need supply aggregation function.","code":"clustree(seurat, prefix = \"res.\",          node_colour = \"Gene730\", node_colour_aggr = \"median\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"overlaying-clustering-trees","dir":"Articles","previous_headings":"","what":"Overlaying clustering trees","title":"Plotting clustering trees","text":"One way think clustering trees add extra dimension data shows clusters “evolve” time (increasing resolution). times can useful overlay dimension dimensions data, particularly come dimensionality reduction techniques. can using clustree_overlay function:  easiest way understand plot imagine looking clustering tree . x y axes chosen dimensions data z axis clustering resolution. cluster node placed mean x y values samples contains. can also see points corresponding individual samples.","code":"clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"choosing-what-to-colour","dir":"Articles","previous_headings":"Overlaying clustering trees","what":"Choosing what to colour","title":"Plotting clustering trees","text":"Due way ggplot2 works can colour one element plot (node points actually use fill aesthetic). default tree edges coloured according clustering resolution originate . Alternatively can choose colour sample points highest resolution cluster. colour whichever element isn’t using colour aesthetic can set using alt_colour argument.  Aesthetics clustering tree nodes can controlled way regular clustree function additional arguments adjusting appearance edges points.","code":"clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\",                  use_colour = \"points\", alt_colour = \"blue\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"labelling-nodes","dir":"Articles","previous_headings":"Overlaying clustering trees","what":"Labelling nodes","title":"Plotting clustering trees","text":"One downsides visualisation can hard identify clusters node represents can often overlap. make bit easier can label node resolution cluster ID.","code":"clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\",                  label_nodes = TRUE)"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"showing-the-side-view","dir":"Articles","previous_headings":"Overlaying clustering trees","what":"Showing the side view","title":"Plotting clustering trees","text":"main overlay plot show us tree can also useful see side, showing one x y dimensions resolution dimension. can get views setting plot_sides option TRUE. return list ggplot objects instead single plot.","code":"overlay_list <- clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\",                                  y_value = \"PC2\", plot_sides = TRUE)  names(overlay_list) #> [1] \"overlay\" \"x_side\"  \"y_side\"  overlay_list$x_side overlay_list$y_side"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"modifying-appearance","dir":"Articles","previous_headings":"","what":"Modifying appearance","title":"Plotting clustering trees","text":"clustree() function returns ggplot object can modified using functions {ggplot2} {ggraph} packages. example change colour scales used nodes edges:","code":"clustree(nba_clusts, prefix = \"K\") +     scale_color_brewer(palette = \"Set1\") +     scale_edge_color_continuous(low = \"blue\", high = \"red\") #> Scale for edge_colour is already present. #> Adding another scale for edge_colour, which will replace the existing scale."},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"legends","dir":"Articles","previous_headings":"Modifying appearance","what":"Legends","title":"Plotting clustering trees","text":"way ggplot objects displayed relative size plotting window output file. main plot always fit sometimes legends placed outside visible area. One solution simply increase size image. alternative solution turn legends, either setting aesthetics static values using guides function. also move somewhere might fit better. example let’s remove edge legends move rest bottom:","code":"clustree(nba_clusts, prefix = \"K\") +     guides(edge_colour = FALSE, edge_alpha = FALSE) +     theme(legend.position = \"bottom\") #> Warning: The `<scale>` argument of `guides()` cannot be `FALSE`. Use \"none\" instead as #> of ggplot2 3.3.4. #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was #> generated."},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"citing-clustree","dir":"Articles","previous_headings":"","what":"Citing clustree","title":"Plotting clustering trees","text":"find {clustree} clustering trees approach useful work please cite associated publication:","code":"citation(\"clustree\") #> To cite package 'clustree' in publications use: #>  #>   Zappia L, Oshlack A. Clustering trees: a visualization for evaluating #>   clusterings at multiple resolutions. Gigascience. 2018;7. #>   DOI:gigascience/giy083 #>  #> A BibTeX entry for LaTeX users is #>  #>   @Article{, #>     author = {Luke Zappia and Alicia Oshlack}, #>     title = {Clustering trees: a visualization for evaluating clusterings at #>              multiple resolutions}, #>     journal = {GigaScience}, #>     volume = {7}, #>     number = {7}, #>     month = {jul}, #>     year = {2018}, #>     url = {https://doi.org/10.1093/gigascience/giy083}, #>     doi = {10.1093/gigascience/giy083}, #>   }"},{"path":[]},{"path":"https://lazappi.github.io/clustree/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Luke Zappia. Author, maintainer. Alicia Oshlack. Author. Andrea Rau. Contributor. Paul Hoffman. Contributor.","code":""},{"path":"https://lazappi.github.io/clustree/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Zappia L, Oshlack . Clustering trees: visualization evaluating clusterings multiple resolutions. Gigascience. 2018;7. DOI:gigascience/giy083","code":"@Article{,   author = {Luke Zappia and Alicia Oshlack},   title = {Clustering trees: a visualization for evaluating clusterings at              multiple resolutions},   journal = {GigaScience},   volume = {7},   number = {7},   month = {jul},   year = {2018},   url = {https://doi.org/10.1093/gigascience/giy083},   doi = {10.1093/gigascience/giy083}, }"},{"path":"https://lazappi.github.io/clustree/index.html","id":"clustree-","dir":"","previous_headings":"","what":"Visualise Clusterings at Different Resolutions","title":"Visualise Clusterings at Different Resolutions","text":"[]https://app.codecov.io/github/lazappi/clustree?branch=master) Deciding resolution use can difficult question approaching clustering analysis. One way approach problem look samples move number clusters increases. package allows produce clustering trees, visualisation interrogating clusterings resolution increases.","code":""},{"path":"https://lazappi.github.io/clustree/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Visualise Clusterings at Different Resolutions","text":"can install release version clustree CRAN : want use development version can installed GitHub using remotes package: also build vignettes use: NOTE: Building vignettes requires installation additional packages.","code":"install.packages(\"clustree\") # install.packages(\"remotes\") remotes::install_github(\"lazappi/clustree@develop\") # install.packages(\"remotes\") remotes::install_github(\"lazappi/clustree@develop\", dependencies = TRUE,                          build_vignettes = TRUE)"},{"path":"https://lazappi.github.io/clustree/index.html","id":"documentation","dir":"","previous_headings":"","what":"Documentation","title":"Visualise Clusterings at Different Resolutions","text":"documentation clustree available CRAN https://cran.r-project.org/package=clustree. view vignette package documentation development version visit http://lazappi.github.io/clustree.","code":""},{"path":"https://lazappi.github.io/clustree/index.html","id":"citing-clustree","dir":"","previous_headings":"","what":"Citing clustree","title":"Visualise Clusterings at Different Resolutions","text":"use clustree clustering trees approach work please cite publication “Zappia L, Oshlack . Clustering trees: visualization evaluating clusterings multiple resolutions. Gigascience. 2018;7. DOI:gigascience/giy083.","code":"citation(\"clustree\")      Zappia L, Oshlack A. Clustering trees: a visualization for    evaluating clusterings at multiple resolutions. GigaScience.    2018;7. DOI:gigascience/giy083   A BibTeX entry for LaTeX users is      @Article{,      author = {Luke Zappia and Alicia Oshlack},      title = {Clustering trees: a visualization for evaluating clusterings at               multiple resolutions},      journal = {GigaScience},      volume = {7},      number = {7},      month = {jul},      year = {2018},      url = {http://dx.doi.org/10.1093/gigascience/giy083},      doi = {10.1093/gigascience/giy083},    }"},{"path":"https://lazappi.github.io/clustree/index.html","id":"contributors","dir":"","previous_headings":"","what":"Contributors","title":"Visualise Clusterings at Different Resolutions","text":"Thank everyone contributed code clustree package: @andreamrau - added edge_arrow_ends option @mojaveazure - added support Seurat v3 objects","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_labels.html","id":null,"dir":"Reference","previous_headings":"","what":"Add node labels — add_node_labels","title":"Add node labels — add_node_labels","text":"Add node labels clustering tree plot specified aesthetics.","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_labels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add node labels — add_node_labels","text":"","code":"add_node_labels(   node_label,   node_colour,   node_label_size,   node_label_colour,   node_label_nudge,   allowed )"},{"path":"https://lazappi.github.io/clustree/reference/add_node_labels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add node labels — add_node_labels","text":"node_label name metadata column node labels node_colour either value indicating colour use nodes name metadata column colour nodes node_label_size size node label text node_label_colour colour node_label text node_label_nudge numeric value giving nudge y direction node labels allowed vector allowed node attributes use aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_points.html","id":null,"dir":"Reference","previous_headings":"","what":"Add node points — add_node_points","title":"Add node points — add_node_points","text":"Add node points clustering tree plot specified aesthetics.","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_points.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add node points — add_node_points","text":"","code":"add_node_points(node_colour, node_size, node_alpha, allowed)"},{"path":"https://lazappi.github.io/clustree/reference/add_node_points.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add node points — add_node_points","text":"node_colour either value indicating colour use nodes name metadata column colour nodes node_size either numeric value giving size nodes name metadata column use node sizes node_alpha either numeric value giving alpha nodes name metadata column use node transparency allowed vector allowed node attributes use aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Aggregate metadata — aggr_metadata","title":"Aggregate metadata — aggr_metadata","text":"Aggregate metadata column get summarized value cluster node","code":""},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aggregate metadata — aggr_metadata","text":"","code":"aggr_metadata(node_data, col_name, col_aggr, metadata, is_cluster)"},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aggregate metadata — aggr_metadata","text":"node_data data.frame containing information set cluster nodes col_name name metadata column aggregate col_aggr string naming function used aggregate column metadata data.frame providing metadata samples is_cluster logical vector indicating rows metadata node summarized","code":""},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aggregate metadata — aggr_metadata","text":"data.frame aggregated data","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_colour_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert colour node aesthetics — assert_colour_node_aes","title":"Assert colour node aesthetics — assert_colour_node_aes","text":"Raise error incorrect set colour node parameters supplied.","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_colour_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert colour node aesthetics — assert_colour_node_aes","text":"","code":"assert_colour_node_aes(   node_aes_name,   prefix,   metadata,   node_aes,   node_aes_aggr,   min,   max )"},{"path":"https://lazappi.github.io/clustree/reference/assert_colour_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert colour node aesthetics — assert_colour_node_aes","text":"node_aes_name name node aesthetic check prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes value node aesthetic check node_aes_aggr aggregation function associated node aesthetic min minimum numeric value allowed max maximum numeric value allowed","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert node aesthetics — assert_node_aes","title":"Assert node aesthetics — assert_node_aes","text":"Raise error incorrect set node parameters supplied.","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert node aesthetics — assert_node_aes","text":"","code":"assert_node_aes(node_aes_name, prefix, metadata, node_aes, node_aes_aggr)"},{"path":"https://lazappi.github.io/clustree/reference/assert_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert node aesthetics — assert_node_aes","text":"node_aes_name name node aesthetic check prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes value node aesthetic check node_aes_aggr aggregation function associated node aesthetic","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_numeric_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert numeric node aesthetics — assert_numeric_node_aes","title":"Assert numeric node aesthetics — assert_numeric_node_aes","text":"Raise error incorrect set numeric node parameters supplied.","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_numeric_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert numeric node aesthetics — assert_numeric_node_aes","text":"","code":"assert_numeric_node_aes(   node_aes_name,   prefix,   metadata,   node_aes,   node_aes_aggr,   min,   max )"},{"path":"https://lazappi.github.io/clustree/reference/assert_numeric_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert numeric node aesthetics — assert_numeric_node_aes","text":"node_aes_name name node aesthetic check prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes value node aesthetic check node_aes_aggr aggregation function associated node aesthetic min minimum numeric value allowed max maximum numeric value allowed","code":""},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":null,"dir":"Reference","previous_headings":"","what":"Build tree graph — build_tree_graph","title":"Build tree graph — build_tree_graph","text":"Build tree graph set clusterings, metadata associated aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Build tree graph — build_tree_graph","text":"","code":"build_tree_graph(   clusterings,   prefix,   count_filter,   prop_filter,   metadata,   node_aes_list )"},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Build tree graph — build_tree_graph","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution prefix string indicating columns containing clustering information count_filter count threshold filtering edges clustering graph prop_filter proportion threshold filtering edges clustering graph metadata data.frame containing metadata sample can used node aesthetics node_aes_list nested list containing node aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Build tree graph — build_tree_graph","text":"tidygraph::tbl_graph object containing tree graph","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate SC3 stability — calc_sc3_stability","title":"Calculate SC3 stability — calc_sc3_stability","text":"Calculate SC3 stability index every cluster every resolution set clusterings. index varies 0 1, 1 suggests cluster stable across resolutions. See calc_sc3_stability_cluster() details.","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate SC3 stability — calc_sc3_stability","text":"","code":"calc_sc3_stability(clusterings)"},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate SC3 stability — calc_sc3_stability","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate SC3 stability — calc_sc3_stability","text":"matrix stability score cluster","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate single SC3 stability — calc_sc3_stability_cluster","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"Calculate SC3 stability index single cluster set clusterings. index varies 0 1, 1 suggests cluster stable across resolutions.","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"","code":"calc_sc3_stability_cluster(clusterings, res, cluster)"},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution res resolution cluster calculate stability cluster index cluster calculate stability ","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"SC3 stability index","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"index originally introduced SC3 package clustering single-cell RNA-seq data. Clusters awarded increased stability share samples cluster another resolution penalised higher resolutions. use slightly different notation describe score results : $$   s(c_{k, }) =   \\frac{1}{size(L) + 1}   \\sum_{l \\L}     \\sum_{j \\N_l}       \\frac{size(c_{k, } \\cap c_{l, j})}{size(c_{l, j}) * size(N_l) ^ 2} $$ : c_{x, y} cluster y resolution x k resolution cluster want score index cluster want score L set resolutions except k l resolution L N_l set clusters resolution l share samples c_{k, } j cluster N_l","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":null,"dir":"Reference","previous_headings":"","what":"Check node aes list — check_node_aes_list","title":"Check node aes list — check_node_aes_list","text":"Warn node aesthetic names incorrect","code":""},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check node aes list — check_node_aes_list","text":"","code":"check_node_aes_list(node_aes_list)"},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check node aes list — check_node_aes_list","text":"node_aes_list List node aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check node aes list — check_node_aes_list","text":"Corrected node aesthetics list","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree-package.html","id":null,"dir":"Reference","previous_headings":"","what":"Clustree — clustree-package","title":"Clustree — clustree-package","text":"Deciding resolution use can difficult question approaching clustering analysis. One way approach problem look samples move number clusters increases. package allows produce clustering trees, visualisation interrogating clusterings resolution increases.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a clustering tree — clustree","title":"Plot a clustering tree — clustree","text":"Creates plot clustering tree showing relationship clusterings different resolutions.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a clustering tree — clustree","text":"","code":"clustree(x, ...)  # S3 method for matrix clustree(   x,   prefix,   suffix = NULL,   metadata = NULL,   count_filter = 0,   prop_filter = 0.1,   layout = c(\"tree\", \"sugiyama\"),   use_core_edges = TRUE,   highlight_core = FALSE,   node_colour = prefix,   node_colour_aggr = NULL,   node_size = \"size\",   node_size_aggr = NULL,   node_size_range = c(4, 15),   node_alpha = 1,   node_alpha_aggr = NULL,   node_text_size = 3,   scale_node_text = FALSE,   node_text_colour = \"black\",   node_text_angle = 0,   node_label = NULL,   node_label_aggr = NULL,   node_label_size = 3,   node_label_nudge = -0.2,   edge_width = 1.5,   edge_arrow = TRUE,   edge_arrow_ends = c(\"last\", \"first\", \"both\"),   show_axis = FALSE,   return = c(\"plot\", \"graph\", \"layout\"),   ... )  # S3 method for data.frame clustree(x, prefix, ...)  # S3 method for SingleCellExperiment clustree(x, prefix, exprs = \"counts\", ...)  # S3 method for seurat clustree(x, prefix = \"res.\", exprs = c(\"data\", \"raw.data\", \"scale.data\"), ...)  # S3 method for Seurat clustree(   x,   prefix = paste0(assay, \"_snn_res.\"),   exprs = c(\"data\", \"counts\", \"scale.data\"),   assay = NULL,   ... )"},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a clustering tree — clustree","text":"x object containing clustering data ... extra parameters passed methods prefix string indicating columns containing clustering information suffix string end column names containing clustering information metadata data.frame containing metadata sample can used node aesthetics count_filter count threshold filtering edges clustering graph prop_filter proportion threshold filtering edges clustering graph layout string specifying \"tree\" \"sugiyama\" layout, see igraph::layout_as_tree() igraph::layout_with_sugiyama() details use_core_edges logical, whether use core tree (edges maximum proportion node) creating graph layout, (unfiltered) edges still displayed highlight_core logical, whether increase edge width core network make easier see node_colour either value indicating colour use nodes name metadata column colour nodes node_colour_aggr node_colour column name string giving name function aggregate column samples cluster node_size either numeric value giving size nodes name metadata column use node sizes node_size_aggr node_size column name string giving name function aggregate column samples cluster node_size_range numeric vector length two giving maximum minimum point size plotting nodes node_alpha either numeric value giving alpha nodes name metadata column use node transparency node_alpha_aggr node_aggr column name string giving name function aggregate column samples cluster node_text_size numeric value giving size node text scale_node_text FALSE scale_node_text logical indicating whether scale node text along node size node_text_colour colour value node text (label) node_text_angle rotation node text node_label additional label add nodes node_label_aggr node_label column name string giving name function aggregate column samples cluster node_label_size numeric value giving size node label text node_label_nudge numeric value giving nudge y direction node labels edge_width numeric value giving width plotted edges edge_arrow logical indicating whether add arrow edges edge_arrow_ends string indicating ends line draw arrow heads edge_arrow TRUE, one \"last\", \"first\", \"\" show_axis whether show resolution axis return string specifying return, either \"plot\" (ggplot object), \"graph\" (tbl_graph object) \"layout\" (ggraph layout object) exprs source gene expression information use node aesthetics, SingleCellExperiment objects must name assayNames(x), seurat object must one data, raw.data scale.data Seurat object must one data, counts scale.data assay name assay pull expression clustering data Seurat objects","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a clustering tree — clustree","text":"ggplot object (default), tbl_graph object ggraph layout object depending value return","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a clustering tree — clustree","text":"Data sources Plotting clustering tree requires information cluster sample assigned different resolutions. information can supplied various forms, matrix, data.frame specialised object. cases object provided must contain numeric columns naming structure PXS P prefix indicating column contains clustering information, X numeric value indicating clustering resolution S additional suffix removed. SingleCellExperiment objects information must colData slot Seurat objects must meta.data slot. objects except matrices additional columns can used aesthetics, matrices additional metadata data.frame can supplied required. Filtering Edges graph can filtered adjusting count_filter prop_filter parameters. count_filter removes edges represent less number samples, prop_filter removes edges represent less proportion cells node points towards. Node aesthetics aesthetics plotted nodes can controlled various ways. default colour indicates clustering resolution, size indicates number samples cluster transparency set 100%. can set specific value linked supplied metadata column. SingleCellExperiment Seurat object names genes can also used. metadata column used aggregation function must also supplied combine samples cluster. function must take vector values return single value. Layout clustering tree can displayed using either Reingold-Tilford tree layout algorithm Sugiyama layout algorithm layered directed acyclic graphs. layouts selected algorithms available igraph package designed trees. Reingold-Tilford algorithm places children parents Sugiyama places nodes layers trying minimise number crossing edges. See igraph::layout_as_tree() igraph::layout_with_sugiyama() details. use_core_edges TRUE (default) core tree maximum proportion edges node used constructing layout. can often lead attractive layouts core tree visible.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a clustering tree — clustree","text":"","code":"data(nba_clusts) clustree(nba_clusts, prefix = \"K\")"},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":null,"dir":"Reference","previous_headings":"","what":"Overlay a clustering tree — clustree_overlay","title":"Overlay a clustering tree — clustree_overlay","text":"Creates plot clustering tree overlaid scatter plot individual samples.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Overlay a clustering tree — clustree_overlay","text":"","code":"clustree_overlay(x, ...)  # S3 method for matrix clustree_overlay(   x,   prefix,   metadata,   x_value,   y_value,   suffix = NULL,   count_filter = 0,   prop_filter = 0.1,   node_colour = prefix,   node_colour_aggr = NULL,   node_size = \"size\",   node_size_aggr = NULL,   node_size_range = c(4, 15),   node_alpha = 1,   node_alpha_aggr = NULL,   edge_width = 1,   use_colour = c(\"edges\", \"points\"),   alt_colour = \"black\",   point_size = 3,   point_alpha = 0.2,   point_shape = 18,   label_nodes = FALSE,   label_size = 3,   plot_sides = FALSE,   side_point_jitter = 0.45,   side_point_offset = 1,   ... )  # S3 method for data.frame clustree_overlay(x, prefix, ...)  # S3 method for SingleCellExperiment clustree_overlay(   x,   prefix,   x_value,   y_value,   exprs = \"counts\",   red_dim = NULL,   ... )  # S3 method for seurat clustree_overlay(   x,   x_value,   y_value,   prefix = \"res.\",   exprs = c(\"data\", \"raw.data\", \"scale.data\"),   red_dim = NULL,   ... )  # S3 method for Seurat clustree_overlay(   x,   x_value,   y_value,   prefix = paste0(assay, \"_snn_res.\"),   exprs = c(\"data\", \"counts\", \"scale.data\"),   red_dim = NULL,   assay = NULL,   ... )"},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Overlay a clustering tree — clustree_overlay","text":"x object containing clustering data ... extra parameters passed methods prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics x_value numeric metadata column use x axis y_value numeric metadata column use y axis suffix string end column names containing clustering information count_filter count threshold filtering edges clustering graph prop_filter proportion threshold filtering edges clustering graph node_colour either value indicating colour use nodes name metadata column colour nodes node_colour_aggr node_colour column name string giving name function aggregate column samples cluster node_size either numeric value giving size nodes name metadata column use node sizes node_size_aggr node_size column name string giving name function aggregate column samples cluster node_size_range numeric vector length two giving maximum minimum point size plotting nodes node_alpha either numeric value giving alpha nodes name metadata column use node transparency node_alpha_aggr node_aggr column name string giving name function aggregate column samples cluster edge_width numeric value giving width plotted edges use_colour one \"edges\" \"points\" specifying element apply colour aesthetic alt_colour colour value used edges points (whichever given use_colour) point_size numeric value giving size sample points point_alpha numeric value giving alpha sample points point_shape numeric value giving shape sample points label_nodes logical value indicating whether add labels clustering graph nodes label_size numeric value giving size node labels label_nodes TRUE plot_sides logical value indicating whether produce side plots side_point_jitter numeric value giving y-direction spread points side plots side_point_offset numeric value giving y-direction offset points side plots exprs source gene expression information use node aesthetics, SingleCellExperiment objects must name assayNames(x), seurat object must one data, raw.data scale.data Seurat object must one data, counts scale.data red_dim dimensionality reduction use source x_value y_value assay name assay pull expression clustering data Seurat objects","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Overlay a clustering tree — clustree_overlay","text":"ggplot object plot_sides FALSE list ggplot objects plot_sides TRUE","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Overlay a clustering tree — clustree_overlay","text":"Data sources Plotting clustering tree requires information cluster sample assigned different resolutions. information can supplied various forms, matrix, data.frame specialised object. cases object provided must contain numeric columns naming structure PXS P prefix indicating column contains clustering information, X numeric value indicating clustering resolution S additional suffix removed. SingleCellExperiment objects information must colData slot Seurat objects must meta.data slot. objects except matrices additional columns can used aesthetics. Filtering Edges graph can filtered adjusting count_filter prop_filter parameters. count_filter removes edges represent less number samples, prop_filter removes edges represent less proportion cells node points towards. Node aesthetics aesthetics plotted nodes can controlled various ways. default colour indicates clustering resolution, size indicates number samples cluster transparency set 100%. can set specific value linked supplied metadata column. SingleCellExperiment Seurat object names genes can also used. metadata column used aggregation function must also supplied combine samples cluster. function must take vector values return single value. Colour aesthetic colour aesthetic can applied either edges sample points setting use_colour. \"edges\" selected edges coloured according clustering resolution originate . \"points\" selected coloured according cluster assigned highest resolution. Dimensionality reductions SingleCellExperiment Seurat objects precomputed dimensionality reductions can used x y aesthetics. red_dim must set name dimensionality reduction reducedDimNames(x) (SingleCellExperiment) x@dr (Seurat object). x_value y_value can set red_dimX red_dim matches red_dim argument X column dimensionality reduction use.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Overlay a clustering tree — clustree_overlay","text":"","code":"data(nba_clusts) clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\")"},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":null,"dir":"Reference","previous_headings":"","what":"Get tree edges — get_tree_edges","title":"Get tree edges — get_tree_edges","text":"Extract edges set clusterings","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get tree edges — get_tree_edges","text":"","code":"get_tree_edges(clusterings, prefix)"},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get tree edges — get_tree_edges","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution prefix string indicating columns containing clustering information","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get tree edges — get_tree_edges","text":"data.frame containing edge information","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":null,"dir":"Reference","previous_headings":"","what":"Get tree nodes — get_tree_nodes","title":"Get tree nodes — get_tree_nodes","text":"Extract nodes set clusterings add relevant attributes","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get tree nodes — get_tree_nodes","text":"","code":"get_tree_nodes(clusterings, prefix, metadata, node_aes_list)"},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get tree nodes — get_tree_nodes","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes_list nested list containing node aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get tree nodes — get_tree_nodes","text":"data.frame containing node information","code":""},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":null,"dir":"Reference","previous_headings":"","what":"Clustered NBA positions dataset — nba_clusts","title":"Clustered NBA positions dataset — nba_clusts","text":"NBA positions dataset clustered using k-means range values k","code":""},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Clustered NBA positions dataset — nba_clusts","text":"","code":"nba_clusts"},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Clustered NBA positions dataset — nba_clusts","text":"nba_clusts data.frame containing NBA positions dataset additional columns holding k-means clusterings different values k first two principal components Position - Player position TurnoverPct - Turnover percentage ReboundPct - Rebound percentage AssistPct - Assist percentage FieldGoalPct - Field goal percentage K1 - K5 - Results k-means clustering PC1 - First principal component PC2 - Second principal component","code":""},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Clustered NBA positions dataset — nba_clusts","text":"NBA positions downloaded https://github.com/lazappi/nba_positions. source dataset available Kaggle https://www.kaggle.com/drgilermo/nba-players-stats/data?select=Seasons_Stats.csv originally scraped Basketball Reference. See https://github.com/lazappi/clustree/blob/master/data-raw/nba_clusts.R details clustering performed.","code":""},{"path":"https://lazappi.github.io/clustree/reference/overlay_node_points.html","id":null,"dir":"Reference","previous_headings":"","what":"Overlay node points — overlay_node_points","title":"Overlay node points — overlay_node_points","text":"Overlay clustering tree nodes scatter plot specified aesthetics.","code":""},{"path":"https://lazappi.github.io/clustree/reference/overlay_node_points.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Overlay node points — overlay_node_points","text":"","code":"overlay_node_points(   nodes,   x_value,   y_value,   node_colour,   node_size,   node_alpha )"},{"path":"https://lazappi.github.io/clustree/reference/overlay_node_points.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Overlay node points — overlay_node_points","text":"nodes data.frame describing nodes x_value column nodes use x position y_value column nodes use y position node_colour either value indicating colour use nodes name metadata column colour nodes node_size either numeric value giving size nodes name metadata column use node sizes node_alpha either numeric value giving alpha nodes name metadata column use node transparency","code":""},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot overlay side — plot_overlay_side","title":"Plot overlay side — plot_overlay_side","text":"Plot side view clustree overlay plot. ordinary plot shows tree plot shows side, highlighting either x y dimension clustering resolution.","code":""},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot overlay side — plot_overlay_side","text":"","code":"plot_overlay_side(   nodes,   edges,   points,   prefix,   side_value,   graph_attr,   node_size_range,   edge_width,   use_colour,   alt_colour,   point_size,   point_alpha,   point_shape,   label_nodes,   label_size,   y_jitter,   y_offset )"},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot overlay side — plot_overlay_side","text":"nodes data.frame describing nodes edges data.frame describing edges points data.frame describing points prefix string indicating columns containing clustering information side_value string giving metadata column use x axis graph_attr list describing graph attributes node_size_range numeric vector length two giving maximum minimum point size plotting nodes edge_width numeric value giving width plotted edges use_colour one \"edges\" \"points\" specifying element apply colour aesthetic alt_colour colour value used edges points (whichever given use_colour) point_size numeric value giving size sample points point_alpha numeric value giving alpha sample points point_shape numeric value giving shape sample points label_nodes logical value indicating whether add labels clustering graph nodes label_size numeric value giving size node labels label_nodes TRUE y_jitter numeric value giving y-direction spread points side plots y_offset numeric value giving y-direction offset points side plots","code":""},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot overlay side — plot_overlay_side","text":"ggplot object","code":""},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated scRNA-seq dataset — sc_example","title":"Simulated scRNA-seq dataset — sc_example","text":"simulated scRNA-seq dataset generated using splatter package clustered using SC3 Seurat packages.","code":""},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated scRNA-seq dataset — sc_example","text":"","code":"sc_example"},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated scRNA-seq dataset — sc_example","text":"sc_example list holding simulated scRNA-seq dataset. Items list included simulated counts, normalised log counts, tSNE dimensionality reduction cell assignments SC3 Seurat clustering.","code":""},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Simulated scRNA-seq dataset — sc_example","text":"","code":"# Simulation library(\"splatter\") # Version 1.2.1  sim <- splatSimulate(batchCells = 200, nGenes = 10000,                      group.prob = c(0.4, 0.2, 0.2, 0.15, 0.05),                      de.prob = c(0.1, 0.2, 0.05, 0.1, 0.05),                      method = \"groups\", seed = 1) sim_counts <- counts(sim)[1:1000, ]  # SC3 Clustering library(\"SC3\") # Version 1.7.6 library(\"scater\") # Version 1.6.2  sim_sc3 <- SingleCellExperiment(assays = list(counts = sim_counts)) rowData(sim_sc3)$feature_symbol <- rownames(sim_counts) sim_sc3 <- normalise(sim_sc3) sim_sc3 <- sc3(sim_sc3, ks = 1:8, biology = FALSE, n_cores = 1) sim_sc3 <- runTSNE(sim_sc3)  # Seurat Clustering library(\"Seurat\") # Version 2.2.0  sim_seurat <- CreateSeuratObject(sim_counts) sim_seurat <- NormalizeData(sim_seurat, display.progress = FALSE) sim_seurat <- FindVariableGenes(sim_seurat, do.plot = FALSE,                                 display.progress = FALSE) sim_seurat <- ScaleData(sim_seurat, display.progress = FALSE) sim_seurat <- RunPCA(sim_seurat, do.print = FALSE) sim_seurat <- FindClusters(sim_seurat, dims.use = 1:6,                            resolution = seq(0, 1, 0.1),                            print.output = FALSE)  sc_example <- list(counts = counts(sim_sc3),                    logcounts = logcounts(sim_sc3),                    tsne = reducedDim(sim_sc3),                    sc3_clusters = as.data.frame(colData(sim_sc3)),                    seurat_clusters = sim_seurat@meta.data)"},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Store node aesthetics — store_node_aes","title":"Store node aesthetics — store_node_aes","text":"Store names node attributes use aesthetics graph attributes","code":""},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Store node aesthetics — store_node_aes","text":"","code":"store_node_aes(graph, node_aes_list, metadata)"},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Store node aesthetics — store_node_aes","text":"graph graph store attributes node_aes_list nested list containing node aesthetics metadata data.frame containing metadata can used aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Store node aesthetics — store_node_aes","text":"graph additional attributes","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-051-2023-11-05","dir":"Changelog","previous_headings":"","what":"clustree 0.5.1 (2023-11-05)","title":"clustree 0.5.1 (2023-11-05)","text":"Minor updates compatibility Seurat >= 5.0.0 ggplot2 >= 3.4.0","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-5-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.5.0.9001 (2023-10-24)","title":"clustree 0.5.1 (2023-11-05)","text":"Avoid warnings due deprecated functionality ggplot2 tidyselect. Includes increasing ggplot2 requirement >= 3.4.0. (Fixes #35)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-5-1-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.5.0.9000 (2023-10-24)","title":"clustree 0.5.1 (2023-11-05)","text":"Minor updates compatibility upcoming Seurat v5 release (Fixes #93)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-050-2022-06-24","dir":"Changelog","previous_headings":"","what":"clustree 0.5.0 (2022-06-24)","title":"clustree 0.5.0 (2022-06-24)","text":"CRAN release: 2022-06-25","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"minor-changes-0-5-0","dir":"Changelog","previous_headings":"","what":"Minor changes","title":"clustree 0.5.0 (2022-06-24)","text":"Add node_text_angle argument clustree() (Fixes #79, PR #80)","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-5-0","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.4.9001 (2022-06-24)","title":"clustree 0.5.0 (2022-06-24)","text":"Add node_text_angle argument clustree() (Fixes #79, PR #80)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-044-2021-11-06","dir":"Changelog","previous_headings":"","what":"clustree 0.4.4 (2021-11-06)","title":"clustree 0.4.4 (2021-11-06)","text":"CRAN release: 2021-11-08","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-4-4","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.4.4 (2021-11-06)","text":"Minor changes tests failing due changes Bioconductor 3.14 release Minor updates URLs documentation","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-043-2020-06-12","dir":"Changelog","previous_headings":"","what":"clustree 0.4.3 (2020-06-12)","title":"clustree 0.4.3 (2020-06-12)","text":"CRAN release: 2020-06-14","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-4-3","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.4.3 (2020-06-12)","text":"Fix axis label order clustree() (Fixes #44) Add checks handle features including “-” characters Seurat SingleCellExperiment interfaces clustree() clustree_overlay() (Fixes #43) Change metadata columns extracted compatibility tibble objects (Fixes #52)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"other-changes-0-4-3","dir":"Changelog","previous_headings":"","what":"Other changes","title":"clustree 0.4.3 (2020-06-12)","text":"Replace iris_clusts dataset nba_clusts dataset Increase R dependency > 3.5","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9003 (2020-06-12)","title":"clustree 0.4.3 (2020-06-12)","text":"Change metadata columns extracted compatibility tibble objects (Fixes #52)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9002 (2020-06-12)","title":"clustree 0.4.3 (2020-06-12)","text":"Replace iris_clusts dataset nba_clusts dataset","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3-2","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9001 (2020-03-20)","title":"clustree 0.4.3 (2020-06-12)","text":"Add checks handle features including “-” characters Seurat SingleCellExperiment interfaces clustree() clustree_overlay() (Fixes #43)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3-3","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9000 (2020-03-19)","title":"clustree 0.4.3 (2020-06-12)","text":"Fix axis label order clustree() (Fixes #44)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-042-2020-01-29","dir":"Changelog","previous_headings":"","what":"clustree 0.4.2 (2020-01-29)","title":"clustree 0.4.2 (2020-01-29)","text":"CRAN release: 2020-01-29","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-4-2","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.4.2 (2020-01-29)","text":"sc_example contained DataFrame rather data.frame SC3 data, now fixed Alpha now represent in_prop values 0 1 Change point colour resolution name determined side plots clustree_overlay() (Fixes #38) Fix missing alpha scale clustree() (Fixes #32) allow matching start column names without wildcard problem Issue #19 Fixes minor bugs discovered new unit tests","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"other-changes-0-4-2","dir":"Changelog","previous_headings":"","what":"Other changes","title":"clustree 0.4.2 (2020-01-29)","text":"Tests matching prefix values Test point colour clustree_overlay() rounded resolutions","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9005 (2020-01-29)","title":"clustree 0.4.2 (2020-01-29)","text":"Add additional unit tests, including missing clustree_overlay() Minor fixes bugs discovered new tests","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9004 (2020-01-28)","title":"clustree 0.4.2 (2020-01-29)","text":"Add additional unit tests","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2-2","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9003 (2020-01-28)","title":"clustree 0.4.2 (2020-01-29)","text":"Add fixed alpha scale range clustree_overlay() (Fixes #41)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2-3","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9002 (2020-01-28)","title":"clustree 0.4.2 (2020-01-29)","text":"Add tests matching prefix values Change prefix matching simpler exact method without regular expressions Add test point colour clustree_overlay() rounded resolutions Change point colour resolution name determined (Fixes #38)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2-4","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9001 (2020-01-27)","title":"clustree 0.4.2 (2020-01-29)","text":"Fix missing alpha scale (Fixes #32)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2-5","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9000 (2020-01-27)","title":"clustree 0.4.2 (2020-01-29)","text":"sc_example contained DataFrame rather data.frame SC3 data","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-041-2019-08-19","dir":"Changelog","previous_headings":"","what":"clustree 0.4.1 (2019-08-19)","title":"clustree 0.4.1 (2019-08-19)","text":"CRAN release: 2019-08-21","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-4-1","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.4.1 (2019-08-19)","text":"Remove requirement clustering matrix numeric (Fixes #33) Fix bug sc3_stability became character character cluster names Keep order cluster names numeric Improve reducedDims accessed SingleCellExperiment objects Fix minor typos documentation","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.0.9002 (2019-08-19)","title":"clustree 0.4.1 (2019-08-19)","text":"Improve reducedDims accessed SingleCellExperiment objects Fix minor typos documentation","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-1-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.0.9001 (2019-06-05)","title":"clustree 0.4.1 (2019-08-19)","text":"Fix bug sc3_stability became character character cluster names Keep order cluster names numeric","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-1-2","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.0.9000 (2019-06-03)","title":"clustree 0.4.1 (2019-08-19)","text":"Remove requirement clustering matrix numeric (Fixes #33)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-040-2019-04-18","dir":"Changelog","previous_headings":"","what":"clustree 0.4.0 (2019-04-18)","title":"clustree 0.4.0 (2019-04-18)","text":"CRAN release: 2019-04-18","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"minor-changes-0-4-0","dir":"Changelog","previous_headings":"","what":"Minor changes","title":"clustree 0.4.0 (2019-04-18)","text":"Add support Seurat v3 objects (thanks @mojaveazure) Add SC3 stability index section vignette (Fixes #28)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-030-2019-02-24","dir":"Changelog","previous_headings":"","what":"clustree 0.3.0 (2019-02-24)","title":"clustree 0.3.0 (2019-02-24)","text":"CRAN release: 2019-02-24","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"minor-changes-0-3-0","dir":"Changelog","previous_headings":"","what":"Minor changes","title":"clustree 0.3.0 (2019-02-24)","text":"Make cluster node attribute factor improve use node colour (Fixes #20) Add show_axis argument displays y-axis resolution values gridlines (Fixes #24) Add ability add additional node labels custom information (Fixes #23) Update CITATION give information GigaScience paper Update README Add custom labels section Add references Add table contents number sections","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-3-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.3.0 (2019-02-24)","text":"Add checks metadata column node aesthetic names (Fixes #15) Use fixed patterns identifying clustering columns data.frames (Fixes #19)","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-3-0","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.3.0.9000 (2019-04-27)","title":"clustree 0.3.0 (2019-02-24)","text":"Add support Seurat v3 objects (thanks @mojaveazure)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-3-0-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.3.0.9001 (2019-04-27)","title":"clustree 0.3.0 (2019-02-24)","text":"Add SC3 stability index section vignette (Fixes #28)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-022-2018-07-10","dir":"Changelog","previous_headings":"","what":"clustree 0.2.2 (2018-07-10)","title":"clustree 0.2.2 (2018-07-10)","text":"CRAN release: 2018-07-10 Replace SingleCellExperiment Seurat example datasets list Add additional checks suggested packages Remove links suggested packages 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(2018-07-09)","title":"clustree 0.2.1 (2018-07-09)","text":"CRAN release: 2018-07-09 Bump version CRAN","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-2-1","dir":"Changelog","previous_headings":"","what":"clustree 0.2.1.9001 (2018-07-10)","title":"clustree 0.2.1 (2018-07-09)","text":"Add additional checks suggested packages Remove links suggested packages documentation","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-2-1-1","dir":"Changelog","previous_headings":"","what":"clustree 0.2.1.9000 (2018-07-10)","title":"clustree 0.2.1 (2018-07-09)","text":"Replace SingleCellExperiment Seurat example datasets list","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-020-2018-06-24","dir":"Changelog","previous_headings":"","what":"clustree 0.2.0 (2018-06-24)","title":"clustree 0.2.0 (2018-06-24)","text":"CRAN release: 2018-06-24 Calculate SC3 stability index cluster nodes Add option use core network calculate layout Add option highlight core network Add option return plot, graph layout Allows overlaying clustering trees data dimensions Store trees tbl_graph instead igraph objects Switch GPL-3 license Updates vignette, documentation tests","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-012-2018-04-11","dir":"Changelog","previous_headings":"","what":"clustree 0.1.2 (2018-04-11)","title":"clustree 0.1.2 (2018-04-11)","text":"CRAN release: 2018-04-20 Adjust tests work new checkmate version (v1.8.6) Update R requirement >= 3.4 (compatibility SingleCellExperiment) Add CITATION file update author entries DESCRIPTION","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-1-2","dir":"Changelog","previous_headings":"","what":"clustree 0.1.2.9000 (2018-05-08)","title":"clustree 0.1.2 (2018-04-11)","text":"Add functions calculate SC3 stability index Switch GPL-3 license","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-1-2-1","dir":"Changelog","previous_headings":"","what":"clustree 0.1.2.9001 (2018-05-09)","title":"clustree 0.1.2 (2018-04-11)","text":"Add option use core network calculate layout Add option highlight core network Add option return plot, graph layout","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-1-2-2","dir":"Changelog","previous_headings":"","what":"clustree 0.1.2.9002 (2018-05-22)","title":"clustree 0.1.2 (2018-04-11)","text":"Store tree tbl_graph instead igraph object Update vignette","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-1-2-3","dir":"Changelog","previous_headings":"","what":"clustree 0.1.2.9003 (2018-06-20)","title":"clustree 0.1.2 (2018-04-11)","text":"Add checks suggested 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resolutions provided Add node text colour option Improve example scRNA-seq datasets","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-0-0-11","dir":"Changelog","previous_headings":"","what":"clustree 0.0.0.9011 (2018-02-09)","title":"clustree 0.0.0 (2018-01-22)","text":"Fix missing node aesthetics static","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-0-0-12","dir":"Changelog","previous_headings":"","what":"clustree 0.0.0.9012 (2018-02-15)","title":"clustree 0.0.0 (2018-01-22)","text":"Switch using function aggregation function names Improve naming aesthetics Set alpha scale limits Add Sugiyama layout Update vignette Tidy code","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-0-0-13","dir":"Changelog","previous_headings":"","what":"clustree 0.0.0.9013 (2018-02-28)","title":"clustree 0.0.0 (2018-01-22)","text":"Fix resolution colour ordering","code":""}]
+[{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"what-is-a-clustering-tree","dir":"Articles","previous_headings":"","what":"What is a clustering tree?","title":"Plotting clustering trees","text":"Clustering analysis used many contexts group similar samples. One problem conducting kind analysis many clusters use. usually controlled parameter provided clustering algorithm, \\(k\\) \\(k\\)-means clustering. Statistics designed help make choice typically either compare two clusterings score single clustering. clustering tree different visualises relationships range resolutions. build clustering tree need look cells move clustering resolution increased. cluster forms node tree edges constructed considering cells cluster lower resolution (say \\(k = 2\\)) end cluster next highest resolution (say \\(k = 3\\)). connecting clusters way can see clusters related , clearly distinct unstable. Extra information cells node can also overlaid order help make decision resolution use. information clustering trees please refer associated publication (Zappia Oshlack 2018).","code":""},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"a-simple-example","dir":"Articles","previous_headings":"","what":"A simple example","title":"Plotting clustering trees","text":"demonstrate clustering tree looks like work short example using nba_clusts dataset.","code":""},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"the-data","dir":"Articles","previous_headings":"A simple example","what":"The data","title":"Plotting clustering trees","text":"nba_clusts dataset consists basic statistics 150 NBA players 2017, 50 three positions (Center, Point Guard Shooting Guards). dataset clustered using \\(k\\)-means different values \\(k\\). information see ?nba_clusts. Let’s load data take look: data.frame player positions statistics (turnover percentage, rebound percentage, assist percentage field goal percentage) well additional columns. columns contain cluster assignments clustering data using \\(k\\)-means values \\(k\\) \\(k = 1\\) \\(k = 5\\).","code":"library(clustree) #> Loading required package: ggraph #> Loading required package: ggplot2 data(\"nba_clusts\")  head(nba_clusts) #>   Position TurnoverPct ReboundPct AssistPct FieldGoalPct K1 K2 K3 K4 K5 #> 1   Center        10.6       17.4      14.7         50.2  1  2  2  1  2 #> 2   Center         9.6       19.6      16.9         46.8  1  2  2  1  2 #> 3   Center        16.0       14.2       5.4         57.1  1  2  2  1  2 #> 4   Center        17.2       14.9       2.7         58.3  1  2  2  1  2 #> 5   Center        11.7       20.8       4.4         55.7  1  2  2  1  2 #> 6   Center        12.5       17.4       7.9         54.5  1  2  2  1  2 #>          PC1       PC2 #> 1  -5.907675 -4.559588 #> 2  -3.398585 -4.015772 #> 3 -14.705825 -3.907384 #> 4 -17.489016 -3.598523 #> 5 -17.705077 -3.455650 #> 6 -13.069032 -3.845442"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"plotting-a-tree","dir":"Articles","previous_headings":"A simple example","what":"Plotting a tree","title":"Plotting clustering trees","text":"clustering information need build clustering tree. column must consist numeric values indicating cluster sample assigned . plot tree just pass information clustree function. also need specify prefix string indicate columns contain clusterings.  can see one cluster distinct change value \\(k\\). Center players different positions. side tree see single cluster splits two clusters expect see. tree becomes messier node multiple incoming edges. good indication clustered data.","code":"clustree(nba_clusts, prefix = \"K\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"controlling-aesthetics","dir":"Articles","previous_headings":"A simple example","what":"Controlling aesthetics","title":"Plotting clustering trees","text":"default size node related number samples cluster colour indicates clustering resolution. Edges coloured according number samples represent transparency shows incoming node proportion, number samples edge divided number samples node points . can control aesthetics setting specific values:  can also link aesthetics information samples. additional columns dataset available added attributes nodes tree. node represents multiple samples need supply aggregation function use well specifying column name. Let’s try colouring nodes according rebound percentage:  can clearly see distinct cluster containing Center players higher rebound percentage average compared clusters.","code":"clustree(nba_clusts, prefix = \"K\", node_colour = \"purple\", node_size = 10,          node_alpha = 0.8) clustree(nba_clusts, prefix = \"K\", node_colour = \"ReboundPct\",          node_colour_aggr = \"mean\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"sc3-stability-index","dir":"Articles","previous_headings":"A simple example > Controlling aesthetics","what":"SC3 stability index","title":"Plotting clustering trees","text":"Apart information dataset can useful display measures clustering quality aesthetics. stability index {SC3} package (Kiselev et al. 2017) measures stability clusters across resolutions automatically calculated clustering tree built. can accessed setting aesthetic \"sc3_stability\" calculated cluster don’t need provide aggregation function. example:","code":"clustree(nba_clusts, prefix = \"K\", node_colour = \"sc3_stability\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"layout","dir":"Articles","previous_headings":"A simple example","what":"Layout","title":"Plotting clustering trees","text":"default tree drawn using Reingold-Tilford tree layout algorithm tries place nodes parents (Reingold Tilford 1981). Alternatively use Sugiyama layout specifying layout argument. algorithm tries minimise number crossing edges (Sugiyama, Tagawa, Toda 1981) can produce attractive trees cases.  layout algorithms clustree() uses slightly modified versions tree default. core network edges, highest -proportion edge node, used creating layout. cases leads attractive trees easier interpret. turn , use edges deciding layout, can set use_core_edges FALSE.","code":"clustree(nba_clusts, prefix = \"K\", layout = \"sugiyama\") clustree(nba_clusts, prefix = \"K\", layout = \"sugiyama\", use_core_edges = FALSE)"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"adding-labels","dir":"Articles","previous_headings":"A simple example","what":"Adding labels","title":"Plotting clustering trees","text":"make easy identify clusters cluster nodes labelled cluster number (controlled using node_text arguments) sometimes useful add labels additional information. done way aesthetics. label nodes maximum assist percentage:  One way can useful assigned labels samples. custom function labels cluster players position, otherwise labels cluster “mixed”:","code":"clustree(nba_clusts, prefix = \"K\", node_label = \"AssistPct\",          node_label_aggr = \"max\") label_position <- function(labels) {     if (length(unique(labels)) == 1) {         position <- as.character(unique(labels))     } else {         position <- \"mixed\"     }     return(position) }  clustree(nba_clusts, prefix = \"K\", node_label = \"Position\",          node_label_aggr = \"label_position\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"clustering-trees-for-scrna-seq-data","dir":"Articles","previous_headings":"","what":"Clustering trees for scRNA-seq data","title":"Plotting clustering trees","text":"Clustering become core tool analysing single-cell RNA-sequencing (scRNA-seq) datasets. datasets contain gene expression measurements hundreds hundreds thousands cells. Often samples come complex tissues containing many types cells clustering used group similar cells together. make easier produce clustering trees kinds datasets provide interfaces objects commonly used analyse scRNA-seq data. clustree package contains example simulated scRNA-seq data clustered using {SC3} {Seurat} (Satija et al. 2015) packages.","code":"data(\"sc_example\") names(sc_example) #> [1] \"counts\"          \"logcounts\"       \"tsne\"            \"sc3_clusters\"    #> [5] \"seurat_clusters\""},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"singlecellexperiment-objects","dir":"Articles","previous_headings":"Clustering trees for scRNA-seq data","what":"SingleCellExperiment objects","title":"Plotting clustering trees","text":"SingleCellExperiment one common objects, used across range Bioconductor packages. Let’s look example, first need convert example dataset SingleCellExperiment object: clustering information held coldata slot. can plot clustering tree way data.frame. case clustering column names contain suffix needs stripped away, pass along well.","code":"#> Warning: replacing previous import 'S4Arrays::makeNindexFromArrayViewport' by #> 'DelayedArray::makeNindexFromArrayViewport' when loading 'SummarizedExperiment' suppressPackageStartupMessages(library(\"SingleCellExperiment\"))  sce <- SingleCellExperiment(assays = list(counts = sc_example$counts,                                           logcounts = sc_example$logcounts),                             colData = sc_example$sc3_clusters,                             reducedDims = SimpleList(TSNE = sc_example$tsne)) head(colData(sce)) #> DataFrame with 6 rows and 8 columns #>       sc3_1_clusters sc3_2_clusters sc3_3_clusters sc3_4_clusters #>             <factor>       <factor>       <factor>       <factor> #> Cell1              1              2              3              4 #> Cell2              1              2              3              2 #> Cell3              1              1              1              1 #> Cell4              1              1              1              3 #> Cell5              1              2              3              4 #> Cell6              1              2              2              2 #>       sc3_5_clusters sc3_6_clusters sc3_7_clusters sc3_8_clusters #>             <factor>       <factor>       <factor>       <factor> #> Cell1              3              2              2              3 #> Cell2              2              1              1              1 #> Cell3              5              4              4              5 #> Cell4              4              3              3              4 #> Cell5              3              2              5              8 #> Cell6              2              1              1              1 clustree(sce, prefix = \"sc3_\", suffix = \"_clusters\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"seurat-objects","dir":"Articles","previous_headings":"Clustering trees for scRNA-seq data","what":"Seurat objects","title":"Plotting clustering trees","text":"Clustering trees can also produced directly Seurat objects. Let’s convert SingleCellExperiment Seurat format: case clustering information held meta.data slot can accessed using [[ operator: can now produce clustering tree using object. example prefix clustering columns res. cases default prefix Seurat automatically used.  Note: example uses newer Seurat object available version 3.0.0 greater Seurat. also interface older seurat object may deprecated future.","code":"suppressPackageStartupMessages(library(\"Seurat\"))  # Create the Seurat object, Seurat >= expects a sparse matrix seurat <- CreateSeuratObject(counts = as(sc_example$counts, \"sparseMatrix\"),                              data = as(sc_example$logcounts, \"sparseMatrix\"),                              meta.data = sc_example$seurat_clusters)  # Add the t-SNE embedding seurat[['TSNE']] <- CreateDimReducObject(embeddings = sc_example$tsne,                                          key = \"tSNE_\") #> Warning: No assay specified, setting assay as RNA by default. #> Warning: No columnames present in cell embeddings, setting to 'tSNE_1:2' head(seurat[[]]) #>          orig.ident nCount_RNA nFeature_RNA nGene nUMI res.0 res.0.1 res.0.2 #> Cell1 SeuratProject       4458          503   503 4458     0       0       0 #> Cell2 SeuratProject       4722          549   549 4722     0       0       0 #> Cell3 SeuratProject       3960          504   504 3960     0       0       0 #> Cell4 SeuratProject       4822          525   525 4822     0       0       0 #> Cell5 SeuratProject       4058          492   492 4058     0       0       0 #> Cell6 SeuratProject       6780          610   610 6780     0       0       0 #>       res.0.3 res.0.4 res.0.5 res.0.6 res.0.7 res.0.8 res.0.9 res.1 #> Cell1       1       1       1       1       0       0       0     0 #> Cell2       1       1       1       1       0       0       0     0 #> Cell3       0       0       0       0       1       1       1     1 #> Cell4       0       0       0       0       1       1       1     1 #> Cell5       1       1       1       1       0       0       0     0 #> Cell6       0       0       0       0       1       1       1     1 clustree(seurat, prefix = \"res.\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"using-genes-as-aesthetics","dir":"Articles","previous_headings":"Clustering trees for scRNA-seq data","what":"Using genes as aesthetics","title":"Plotting clustering trees","text":"well able use additional columns aesthetics can also use expression individual genes. Let’s colour nodes Seurat tree Gene730 (highly variable gene). need supply aggregation function.","code":"clustree(seurat, prefix = \"res.\",          node_colour = \"Gene730\", node_colour_aggr = \"median\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"overlaying-clustering-trees","dir":"Articles","previous_headings":"","what":"Overlaying clustering trees","title":"Plotting clustering trees","text":"One way think clustering trees add extra dimension data shows clusters “evolve” time (increasing resolution). times can useful overlay dimension dimensions data, particularly come dimensionality reduction techniques. can using clustree_overlay function:  easiest way understand plot imagine looking clustering tree . x y axes chosen dimensions data z axis clustering resolution. cluster node placed mean x y values samples contains. can also see points corresponding individual samples.","code":"clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"choosing-what-to-colour","dir":"Articles","previous_headings":"Overlaying clustering trees","what":"Choosing what to colour","title":"Plotting clustering trees","text":"Due way ggplot2 works can colour one element plot (node points actually use fill aesthetic). default tree edges coloured according clustering resolution originate . Alternatively can choose colour sample points highest resolution cluster. colour whichever element isn’t using colour aesthetic can set using alt_colour argument.  Aesthetics clustering tree nodes can controlled way regular clustree function additional arguments adjusting appearance edges points.","code":"clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\",                  use_colour = \"points\", alt_colour = \"blue\")"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"labelling-nodes","dir":"Articles","previous_headings":"Overlaying clustering trees","what":"Labelling nodes","title":"Plotting clustering trees","text":"One downsides visualisation can hard identify clusters node represents can often overlap. make bit easier can label node resolution cluster ID.","code":"clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\",                  label_nodes = TRUE)"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"showing-the-side-view","dir":"Articles","previous_headings":"Overlaying clustering trees","what":"Showing the side view","title":"Plotting clustering trees","text":"main overlay plot show us tree can also useful see side, showing one x y dimensions resolution dimension. can get views setting plot_sides option TRUE. return list ggplot objects instead single plot.","code":"overlay_list <- clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\",                                  y_value = \"PC2\", plot_sides = TRUE)  names(overlay_list) #> [1] \"overlay\" \"x_side\"  \"y_side\"  overlay_list$x_side overlay_list$y_side"},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"modifying-appearance","dir":"Articles","previous_headings":"","what":"Modifying appearance","title":"Plotting clustering trees","text":"clustree() function returns ggplot object can modified using functions {ggplot2} {ggraph} packages. example change colour scales used nodes edges:","code":"clustree(nba_clusts, prefix = \"K\") +     scale_color_brewer(palette = \"Set1\") +     scale_edge_color_continuous(low = \"blue\", high = \"red\") #> Scale for edge_colour is already present. #> Adding another scale for edge_colour, which will replace the existing scale."},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"legends","dir":"Articles","previous_headings":"Modifying appearance","what":"Legends","title":"Plotting clustering trees","text":"way ggplot objects displayed relative size plotting window output file. main plot always fit sometimes legends placed outside visible area. One solution simply increase size image. alternative solution turn legends, either setting aesthetics static values using guides function. also move somewhere might fit better. example let’s remove edge legends move rest bottom:","code":"clustree(nba_clusts, prefix = \"K\") +     guides(edge_colour = FALSE, edge_alpha = FALSE) +     theme(legend.position = \"bottom\") #> Warning: The `<scale>` argument of `guides()` cannot be `FALSE`. Use \"none\" instead as #> of ggplot2 3.3.4. #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was #> generated."},{"path":"https://lazappi.github.io/clustree/articles/clustree.html","id":"citing-clustree","dir":"Articles","previous_headings":"","what":"Citing clustree","title":"Plotting clustering trees","text":"find {clustree} clustering trees approach useful work please cite associated publication:","code":"citation(\"clustree\") #> To cite package 'clustree' in publications use: #>  #>   Zappia L, Oshlack A. Clustering trees: a visualization for evaluating #>   clusterings at multiple resolutions. Gigascience. 2018;7. #>   DOI:gigascience/giy083 #>  #> A BibTeX entry for LaTeX users is #>  #>   @Article{, #>     author = {Luke Zappia and Alicia Oshlack}, #>     title = {Clustering trees: a visualization for evaluating clusterings at #>              multiple resolutions}, #>     journal = {GigaScience}, #>     volume = {7}, #>     number = {7}, #>     month = {jul}, #>     year = {2018}, #>     url = {https://doi.org/10.1093/gigascience/giy083}, #>     doi = {10.1093/gigascience/giy083}, #>   }"},{"path":[]},{"path":"https://lazappi.github.io/clustree/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Luke Zappia. Author, maintainer. Alicia Oshlack. Author. Andrea Rau. Contributor. Paul Hoffman. Contributor.","code":""},{"path":"https://lazappi.github.io/clustree/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Zappia L, Oshlack . Clustering trees: visualization evaluating clusterings multiple resolutions. Gigascience. 2018;7. DOI:gigascience/giy083","code":"@Article{,   author = {Luke Zappia and Alicia Oshlack},   title = {Clustering trees: a visualization for evaluating clusterings at              multiple resolutions},   journal = {GigaScience},   volume = {7},   number = {7},   month = {jul},   year = {2018},   url = {https://doi.org/10.1093/gigascience/giy083},   doi = {10.1093/gigascience/giy083}, }"},{"path":"https://lazappi.github.io/clustree/index.html","id":"clustree-","dir":"","previous_headings":"","what":"Visualise Clusterings at Different Resolutions","title":"Visualise Clusterings at Different Resolutions","text":"[]https://app.codecov.io/github/lazappi/clustree?branch=master) Deciding resolution use can difficult question approaching clustering analysis. One way approach problem look samples move number clusters increases. package allows produce clustering trees, visualisation interrogating clusterings resolution increases.","code":""},{"path":"https://lazappi.github.io/clustree/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Visualise Clusterings at Different Resolutions","text":"can install release version clustree CRAN : want use development version can installed GitHub using remotes package: also build vignettes use: NOTE: Building vignettes requires installation additional packages.","code":"install.packages(\"clustree\") # install.packages(\"remotes\") remotes::install_github(\"lazappi/clustree@develop\") # install.packages(\"remotes\") remotes::install_github(\"lazappi/clustree@develop\", dependencies = TRUE,                          build_vignettes = TRUE)"},{"path":"https://lazappi.github.io/clustree/index.html","id":"documentation","dir":"","previous_headings":"","what":"Documentation","title":"Visualise Clusterings at Different Resolutions","text":"documentation clustree available CRAN https://cran.r-project.org/package=clustree. view vignette package documentation development version visit http://lazappi.github.io/clustree.","code":""},{"path":"https://lazappi.github.io/clustree/index.html","id":"citing-clustree","dir":"","previous_headings":"","what":"Citing clustree","title":"Visualise Clusterings at Different Resolutions","text":"use clustree clustering trees approach work please cite publication “Zappia L, Oshlack . Clustering trees: visualization evaluating clusterings multiple resolutions. Gigascience. 2018;7. DOI:gigascience/giy083.","code":"citation(\"clustree\")      Zappia L, Oshlack A. Clustering trees: a visualization for    evaluating clusterings at multiple resolutions. GigaScience.    2018;7. DOI:gigascience/giy083   A BibTeX entry for LaTeX users is      @Article{,      author = {Luke Zappia and Alicia Oshlack},      title = {Clustering trees: a visualization for evaluating clusterings at               multiple resolutions},      journal = {GigaScience},      volume = {7},      number = {7},      month = {jul},      year = {2018},      url = {http://dx.doi.org/10.1093/gigascience/giy083},      doi = {10.1093/gigascience/giy083},    }"},{"path":"https://lazappi.github.io/clustree/index.html","id":"contributors","dir":"","previous_headings":"","what":"Contributors","title":"Visualise Clusterings at Different Resolutions","text":"Thank everyone contributed code clustree package: @andreamrau - added edge_arrow_ends option @mojaveazure - added support Seurat v3 objects","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_labels.html","id":null,"dir":"Reference","previous_headings":"","what":"Add node labels — add_node_labels","title":"Add node labels — add_node_labels","text":"Add node labels clustering tree plot specified aesthetics.","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_labels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add node labels — add_node_labels","text":"","code":"add_node_labels(   node_label,   node_colour,   node_label_size,   node_label_colour,   node_label_nudge,   allowed )"},{"path":"https://lazappi.github.io/clustree/reference/add_node_labels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add node labels — add_node_labels","text":"node_label name metadata column node labels node_colour either value indicating colour use nodes name metadata column colour nodes node_label_size size node label text node_label_colour colour node_label text node_label_nudge numeric value giving nudge y direction node labels allowed vector allowed node attributes use aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_points.html","id":null,"dir":"Reference","previous_headings":"","what":"Add node points — add_node_points","title":"Add node points — add_node_points","text":"Add node points clustering tree plot specified aesthetics.","code":""},{"path":"https://lazappi.github.io/clustree/reference/add_node_points.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add node points — add_node_points","text":"","code":"add_node_points(node_colour, node_size, node_alpha, allowed)"},{"path":"https://lazappi.github.io/clustree/reference/add_node_points.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add node points — add_node_points","text":"node_colour either value indicating colour use nodes name metadata column colour nodes node_size either numeric value giving size nodes name metadata column use node sizes node_alpha either numeric value giving alpha nodes name metadata column use node transparency allowed vector allowed node attributes use aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Aggregate metadata — aggr_metadata","title":"Aggregate metadata — aggr_metadata","text":"Aggregate metadata column get summarized value cluster node","code":""},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aggregate metadata — aggr_metadata","text":"","code":"aggr_metadata(node_data, col_name, col_aggr, metadata, is_cluster)"},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aggregate metadata — aggr_metadata","text":"node_data data.frame containing information set cluster nodes col_name name metadata column aggregate col_aggr string naming function used aggregate column metadata data.frame providing metadata samples is_cluster logical vector indicating rows metadata node summarized","code":""},{"path":"https://lazappi.github.io/clustree/reference/aggr_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aggregate metadata — aggr_metadata","text":"data.frame aggregated data","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_colour_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert colour node aesthetics — assert_colour_node_aes","title":"Assert colour node aesthetics — assert_colour_node_aes","text":"Raise error incorrect set colour node parameters supplied.","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_colour_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert colour node aesthetics — assert_colour_node_aes","text":"","code":"assert_colour_node_aes(   node_aes_name,   prefix,   metadata,   node_aes,   node_aes_aggr,   min,   max )"},{"path":"https://lazappi.github.io/clustree/reference/assert_colour_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert colour node aesthetics — assert_colour_node_aes","text":"node_aes_name name node aesthetic check prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes value node aesthetic check node_aes_aggr aggregation function associated node aesthetic min minimum numeric value allowed max maximum numeric value allowed","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert node aesthetics — assert_node_aes","title":"Assert node aesthetics — assert_node_aes","text":"Raise error incorrect set node parameters supplied.","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert node aesthetics — assert_node_aes","text":"","code":"assert_node_aes(node_aes_name, prefix, metadata, node_aes, node_aes_aggr)"},{"path":"https://lazappi.github.io/clustree/reference/assert_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert node aesthetics — assert_node_aes","text":"node_aes_name name node aesthetic check prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes value node aesthetic check node_aes_aggr aggregation function associated node aesthetic","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_numeric_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert numeric node aesthetics — assert_numeric_node_aes","title":"Assert numeric node aesthetics — assert_numeric_node_aes","text":"Raise error incorrect set numeric node parameters supplied.","code":""},{"path":"https://lazappi.github.io/clustree/reference/assert_numeric_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert numeric node aesthetics — assert_numeric_node_aes","text":"","code":"assert_numeric_node_aes(   node_aes_name,   prefix,   metadata,   node_aes,   node_aes_aggr,   min,   max )"},{"path":"https://lazappi.github.io/clustree/reference/assert_numeric_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert numeric node aesthetics — assert_numeric_node_aes","text":"node_aes_name name node aesthetic check prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes value node aesthetic check node_aes_aggr aggregation function associated node aesthetic min minimum numeric value allowed max maximum numeric value allowed","code":""},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":null,"dir":"Reference","previous_headings":"","what":"Build tree graph — build_tree_graph","title":"Build tree graph — build_tree_graph","text":"Build tree graph set clusterings, metadata associated aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Build tree graph — build_tree_graph","text":"","code":"build_tree_graph(   clusterings,   prefix,   count_filter,   prop_filter,   metadata,   node_aes_list )"},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Build tree graph — build_tree_graph","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution prefix string indicating columns containing clustering information count_filter count threshold filtering edges clustering graph prop_filter proportion threshold filtering edges clustering graph metadata data.frame containing metadata sample can used node aesthetics node_aes_list nested list containing node aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/build_tree_graph.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Build tree graph — build_tree_graph","text":"tidygraph::tbl_graph object containing tree graph","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate SC3 stability — calc_sc3_stability","title":"Calculate SC3 stability — calc_sc3_stability","text":"Calculate SC3 stability index every cluster every resolution set clusterings. index varies 0 1, 1 suggests cluster stable across resolutions. See calc_sc3_stability_cluster() details.","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate SC3 stability — calc_sc3_stability","text":"","code":"calc_sc3_stability(clusterings)"},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate SC3 stability — calc_sc3_stability","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate SC3 stability — calc_sc3_stability","text":"matrix stability score cluster","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate single SC3 stability — calc_sc3_stability_cluster","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"Calculate SC3 stability index single cluster set clusterings. index varies 0 1, 1 suggests cluster stable across resolutions.","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"","code":"calc_sc3_stability_cluster(clusterings, res, cluster)"},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution res resolution cluster calculate stability cluster index cluster calculate stability ","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"SC3 stability index","code":""},{"path":"https://lazappi.github.io/clustree/reference/calc_sc3_stability_cluster.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate single SC3 stability — calc_sc3_stability_cluster","text":"index originally introduced SC3 package clustering single-cell RNA-seq data. Clusters awarded increased stability share samples cluster another resolution penalised higher resolutions. use slightly different notation describe score results : $$   s(c_{k, }) =   \\frac{1}{size(L) + 1}   \\sum_{l \\L}     \\sum_{j \\N_l}       \\frac{size(c_{k, } \\cap c_{l, j})}{size(c_{l, j}) * size(N_l) ^ 2} $$ : c_{x, y} cluster y resolution x k resolution cluster want score index cluster want score L set resolutions except k l resolution L N_l set clusters resolution l share samples c_{k, } j cluster N_l","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":null,"dir":"Reference","previous_headings":"","what":"Check node aes list — check_node_aes_list","title":"Check node aes list — check_node_aes_list","text":"Warn node aesthetic names incorrect","code":""},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check node aes list — check_node_aes_list","text":"","code":"check_node_aes_list(node_aes_list)"},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check node aes list — check_node_aes_list","text":"node_aes_list List node aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/check_node_aes_list.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check node aes list — check_node_aes_list","text":"Corrected node aesthetics list","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree-package.html","id":null,"dir":"Reference","previous_headings":"","what":"Clustree — clustree-package","title":"Clustree — clustree-package","text":"Deciding resolution use can difficult question approaching clustering analysis. One way approach problem look samples move number clusters increases. package allows produce clustering trees, visualisation interrogating clusterings resolution increases.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a clustering tree — clustree","title":"Plot a clustering tree — clustree","text":"Creates plot clustering tree showing relationship clusterings different resolutions.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a clustering tree — clustree","text":"","code":"clustree(x, ...)  # S3 method for matrix clustree(   x,   prefix,   suffix = NULL,   metadata = NULL,   count_filter = 0,   prop_filter = 0.1,   layout = c(\"tree\", \"sugiyama\"),   use_core_edges = TRUE,   highlight_core = FALSE,   node_colour = prefix,   node_colour_aggr = NULL,   node_size = \"size\",   node_size_aggr = NULL,   node_size_range = c(4, 15),   node_alpha = 1,   node_alpha_aggr = NULL,   node_text_size = 3,   scale_node_text = FALSE,   node_text_colour = \"black\",   node_text_angle = 0,   node_label = NULL,   node_label_aggr = NULL,   node_label_size = 3,   node_label_nudge = -0.2,   edge_width = 1.5,   edge_arrow = TRUE,   edge_arrow_ends = c(\"last\", \"first\", \"both\"),   show_axis = FALSE,   return = c(\"plot\", \"graph\", \"layout\"),   ... )  # S3 method for data.frame clustree(x, prefix, ...)  # S3 method for SingleCellExperiment clustree(x, prefix, exprs = \"counts\", ...)  # S3 method for seurat clustree(x, prefix = \"res.\", exprs = c(\"data\", \"raw.data\", \"scale.data\"), ...)  # S3 method for Seurat clustree(   x,   prefix = paste0(assay, \"_snn_res.\"),   exprs = c(\"data\", \"counts\", \"scale.data\"),   assay = NULL,   ... )"},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a clustering tree — clustree","text":"x object containing clustering data ... extra parameters passed methods prefix string indicating columns containing clustering information suffix string end column names containing clustering information metadata data.frame containing metadata sample can used node aesthetics count_filter count threshold filtering edges clustering graph prop_filter proportion threshold filtering edges clustering graph layout string specifying \"tree\" \"sugiyama\" layout, see igraph::layout_as_tree() igraph::layout_with_sugiyama() details use_core_edges logical, whether use core tree (edges maximum proportion node) creating graph layout, (unfiltered) edges still displayed highlight_core logical, whether increase edge width core network make easier see node_colour either value indicating colour use nodes name metadata column colour nodes node_colour_aggr node_colour column name string giving name function aggregate column samples cluster node_size either numeric value giving size nodes name metadata column use node sizes node_size_aggr node_size column name string giving name function aggregate column samples cluster node_size_range numeric vector length two giving maximum minimum point size plotting nodes node_alpha either numeric value giving alpha nodes name metadata column use node transparency node_alpha_aggr node_aggr column name string giving name function aggregate column samples cluster node_text_size numeric value giving size node text scale_node_text FALSE scale_node_text logical indicating whether scale node text along node size node_text_colour colour value node text (label) node_text_angle rotation node text node_label additional label add nodes node_label_aggr node_label column name string giving name function aggregate column samples cluster node_label_size numeric value giving size node label text node_label_nudge numeric value giving nudge y direction node labels edge_width numeric value giving width plotted edges edge_arrow logical indicating whether add arrow edges edge_arrow_ends string indicating ends line draw arrow heads edge_arrow TRUE, one \"last\", \"first\", \"\" show_axis whether show resolution axis return string specifying return, either \"plot\" (ggplot object), \"graph\" (tbl_graph object) \"layout\" (ggraph layout object) exprs source gene expression information use node aesthetics, SingleCellExperiment objects must name assayNames(x), seurat object must one data, raw.data scale.data Seurat object must one data, counts scale.data assay name assay pull expression clustering data Seurat objects","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a clustering tree — clustree","text":"ggplot object (default), tbl_graph object ggraph layout object depending value return","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot a clustering tree — clustree","text":"Data sources Plotting clustering tree requires information cluster sample assigned different resolutions. information can supplied various forms, matrix, data.frame specialised object. cases object provided must contain numeric columns naming structure PXS P prefix indicating column contains clustering information, X numeric value indicating clustering resolution S additional suffix removed. SingleCellExperiment objects information must colData slot Seurat objects must meta.data slot. objects except matrices additional columns can used aesthetics, matrices additional metadata data.frame can supplied required. Filtering Edges graph can filtered adjusting count_filter prop_filter parameters. count_filter removes edges represent less number samples, prop_filter removes edges represent less proportion cells node points towards. Node aesthetics aesthetics plotted nodes can controlled various ways. default colour indicates clustering resolution, size indicates number samples cluster transparency set 100%. can set specific value linked supplied metadata column. SingleCellExperiment Seurat object names genes can also used. metadata column used aggregation function must also supplied combine samples cluster. function must take vector values return single value. Layout clustering tree can displayed using either Reingold-Tilford tree layout algorithm Sugiyama layout algorithm layered directed acyclic graphs. layouts selected algorithms available igraph package designed trees. Reingold-Tilford algorithm places children parents Sugiyama places nodes layers trying minimise number crossing edges. See igraph::layout_as_tree() igraph::layout_with_sugiyama() details. use_core_edges TRUE (default) core tree maximum proportion edges node used constructing layout. can often lead attractive layouts core tree visible.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a clustering tree — clustree","text":"","code":"data(nba_clusts) clustree(nba_clusts, prefix = \"K\")"},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":null,"dir":"Reference","previous_headings":"","what":"Overlay a clustering tree — clustree_overlay","title":"Overlay a clustering tree — clustree_overlay","text":"Creates plot clustering tree overlaid scatter plot individual samples.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Overlay a clustering tree — clustree_overlay","text":"","code":"clustree_overlay(x, ...)  # S3 method for matrix clustree_overlay(   x,   prefix,   metadata,   x_value,   y_value,   suffix = NULL,   count_filter = 0,   prop_filter = 0.1,   node_colour = prefix,   node_colour_aggr = NULL,   node_size = \"size\",   node_size_aggr = NULL,   node_size_range = c(4, 15),   node_alpha = 1,   node_alpha_aggr = NULL,   edge_width = 1,   use_colour = c(\"edges\", \"points\"),   alt_colour = \"black\",   point_size = 3,   point_alpha = 0.2,   point_shape = 18,   label_nodes = FALSE,   label_size = 3,   plot_sides = FALSE,   side_point_jitter = 0.45,   side_point_offset = 1,   ... )  # S3 method for data.frame clustree_overlay(x, prefix, ...)  # S3 method for SingleCellExperiment clustree_overlay(   x,   prefix,   x_value,   y_value,   exprs = \"counts\",   red_dim = NULL,   ... )  # S3 method for seurat clustree_overlay(   x,   x_value,   y_value,   prefix = \"res.\",   exprs = c(\"data\", \"raw.data\", \"scale.data\"),   red_dim = NULL,   ... )  # S3 method for Seurat clustree_overlay(   x,   x_value,   y_value,   prefix = paste0(assay, \"_snn_res.\"),   exprs = c(\"data\", \"counts\", \"scale.data\"),   red_dim = NULL,   assay = NULL,   ... )"},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Overlay a clustering tree — clustree_overlay","text":"x object containing clustering data ... extra parameters passed methods prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics x_value numeric metadata column use x axis y_value numeric metadata column use y axis suffix string end column names containing clustering information count_filter count threshold filtering edges clustering graph prop_filter proportion threshold filtering edges clustering graph node_colour either value indicating colour use nodes name metadata column colour nodes node_colour_aggr node_colour column name string giving name function aggregate column samples cluster node_size either numeric value giving size nodes name metadata column use node sizes node_size_aggr node_size column name string giving name function aggregate column samples cluster node_size_range numeric vector length two giving maximum minimum point size plotting nodes node_alpha either numeric value giving alpha nodes name metadata column use node transparency node_alpha_aggr node_aggr column name string giving name function aggregate column samples cluster edge_width numeric value giving width plotted edges use_colour one \"edges\" \"points\" specifying element apply colour aesthetic alt_colour colour value used edges points (whichever given use_colour) point_size numeric value giving size sample points point_alpha numeric value giving alpha sample points point_shape numeric value giving shape sample points label_nodes logical value indicating whether add labels clustering graph nodes label_size numeric value giving size node labels label_nodes TRUE plot_sides logical value indicating whether produce side plots side_point_jitter numeric value giving y-direction spread points side plots side_point_offset numeric value giving y-direction offset points side plots exprs source gene expression information use node aesthetics, SingleCellExperiment objects must name assayNames(x), seurat object must one data, raw.data scale.data Seurat object must one data, counts scale.data red_dim dimensionality reduction use source x_value y_value assay name assay pull expression clustering data Seurat objects","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Overlay a clustering tree — clustree_overlay","text":"ggplot object plot_sides FALSE list ggplot objects plot_sides TRUE","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Overlay a clustering tree — clustree_overlay","text":"Data sources Plotting clustering tree requires information cluster sample assigned different resolutions. information can supplied various forms, matrix, data.frame specialised object. cases object provided must contain numeric columns naming structure PXS P prefix indicating column contains clustering information, X numeric value indicating clustering resolution S additional suffix removed. SingleCellExperiment objects information must colData slot Seurat objects must meta.data slot. objects except matrices additional columns can used aesthetics. Filtering Edges graph can filtered adjusting count_filter prop_filter parameters. count_filter removes edges represent less number samples, prop_filter removes edges represent less proportion cells node points towards. Node aesthetics aesthetics plotted nodes can controlled various ways. default colour indicates clustering resolution, size indicates number samples cluster transparency set 100%. can set specific value linked supplied metadata column. SingleCellExperiment Seurat object names genes can also used. metadata column used aggregation function must also supplied combine samples cluster. function must take vector values return single value. Colour aesthetic colour aesthetic can applied either edges sample points setting use_colour. \"edges\" selected edges coloured according clustering resolution originate . \"points\" selected coloured according cluster assigned highest resolution. Dimensionality reductions SingleCellExperiment Seurat objects precomputed dimensionality reductions can used x y aesthetics. red_dim must set name dimensionality reduction reducedDimNames(x) (SingleCellExperiment) x@dr (Seurat object). x_value y_value can set red_dimX red_dim matches red_dim argument X column dimensionality reduction use.","code":""},{"path":"https://lazappi.github.io/clustree/reference/clustree_overlay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Overlay a clustering tree — clustree_overlay","text":"","code":"data(nba_clusts) clustree_overlay(nba_clusts, prefix = \"K\", x_value = \"PC1\", y_value = \"PC2\")"},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":null,"dir":"Reference","previous_headings":"","what":"Get tree edges — get_tree_edges","title":"Get tree edges — get_tree_edges","text":"Extract edges set clusterings","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get tree edges — get_tree_edges","text":"","code":"get_tree_edges(clusterings, prefix)"},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get tree edges — get_tree_edges","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution prefix string indicating columns containing clustering information","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_edges.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get tree edges — get_tree_edges","text":"data.frame containing edge information","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":null,"dir":"Reference","previous_headings":"","what":"Get tree nodes — get_tree_nodes","title":"Get tree nodes — get_tree_nodes","text":"Extract nodes set clusterings add relevant attributes","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get tree nodes — get_tree_nodes","text":"","code":"get_tree_nodes(clusterings, prefix, metadata, node_aes_list)"},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get tree nodes — get_tree_nodes","text":"clusterings numeric matrix containing clustering information, column contains clustering separate resolution prefix string indicating columns containing clustering information metadata data.frame containing metadata sample can used node aesthetics node_aes_list nested list containing node aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/get_tree_nodes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get tree nodes — get_tree_nodes","text":"data.frame containing node information","code":""},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":null,"dir":"Reference","previous_headings":"","what":"Clustered NBA positions dataset — nba_clusts","title":"Clustered NBA positions dataset — nba_clusts","text":"NBA positions dataset clustered using k-means range values k","code":""},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Clustered NBA positions dataset — nba_clusts","text":"","code":"nba_clusts"},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Clustered NBA positions dataset — nba_clusts","text":"nba_clusts data.frame containing NBA positions dataset additional columns holding k-means clusterings different values k first two principal components Position - Player position TurnoverPct - Turnover percentage ReboundPct - Rebound percentage AssistPct - Assist percentage FieldGoalPct - Field goal percentage K1 - K5 - Results k-means clustering PC1 - First principal component PC2 - Second principal component","code":""},{"path":"https://lazappi.github.io/clustree/reference/nba_clusts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Clustered NBA positions dataset — nba_clusts","text":"NBA positions downloaded https://github.com/lazappi/nba_positions. source dataset available Kaggle https://www.kaggle.com/drgilermo/nba-players-stats/data?select=Seasons_Stats.csv originally scraped Basketball Reference. See https://github.com/lazappi/clustree/blob/master/data-raw/nba_clusts.R details clustering performed.","code":""},{"path":"https://lazappi.github.io/clustree/reference/overlay_node_points.html","id":null,"dir":"Reference","previous_headings":"","what":"Overlay node points — overlay_node_points","title":"Overlay node points — overlay_node_points","text":"Overlay clustering tree nodes scatter plot specified aesthetics.","code":""},{"path":"https://lazappi.github.io/clustree/reference/overlay_node_points.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Overlay node points — overlay_node_points","text":"","code":"overlay_node_points(   nodes,   x_value,   y_value,   node_colour,   node_size,   node_alpha )"},{"path":"https://lazappi.github.io/clustree/reference/overlay_node_points.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Overlay node points — overlay_node_points","text":"nodes data.frame describing nodes x_value column nodes use x position y_value column nodes use y position node_colour either value indicating colour use nodes name metadata column colour nodes node_size either numeric value giving size nodes name metadata column use node sizes node_alpha either numeric value giving alpha nodes name metadata column use node transparency","code":""},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot overlay side — plot_overlay_side","title":"Plot overlay side — plot_overlay_side","text":"Plot side view clustree overlay plot. ordinary plot shows tree plot shows side, highlighting either x y dimension clustering resolution.","code":""},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot overlay side — plot_overlay_side","text":"","code":"plot_overlay_side(   nodes,   edges,   points,   prefix,   side_value,   graph_attr,   node_size_range,   edge_width,   use_colour,   alt_colour,   point_size,   point_alpha,   point_shape,   label_nodes,   label_size,   y_jitter,   y_offset )"},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot overlay side — plot_overlay_side","text":"nodes data.frame describing nodes edges data.frame describing edges points data.frame describing points prefix string indicating columns containing clustering information side_value string giving metadata column use x axis graph_attr list describing graph attributes node_size_range numeric vector length two giving maximum minimum point size plotting nodes edge_width numeric value giving width plotted edges use_colour one \"edges\" \"points\" specifying element apply colour aesthetic alt_colour colour value used edges points (whichever given use_colour) point_size numeric value giving size sample points point_alpha numeric value giving alpha sample points point_shape numeric value giving shape sample points label_nodes logical value indicating whether add labels clustering graph nodes label_size numeric value giving size node labels label_nodes TRUE y_jitter numeric value giving y-direction spread points side plots y_offset numeric value giving y-direction offset points side plots","code":""},{"path":"https://lazappi.github.io/clustree/reference/plot_overlay_side.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot overlay side — plot_overlay_side","text":"ggplot object","code":""},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated scRNA-seq dataset — sc_example","title":"Simulated scRNA-seq dataset — sc_example","text":"simulated scRNA-seq dataset generated using splatter package clustered using SC3 Seurat packages.","code":""},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated scRNA-seq dataset — sc_example","text":"","code":"sc_example"},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated scRNA-seq dataset — sc_example","text":"sc_example list holding simulated scRNA-seq dataset. Items list included simulated counts, normalised log counts, tSNE dimensionality reduction cell assignments SC3 Seurat clustering.","code":""},{"path":"https://lazappi.github.io/clustree/reference/sc_example.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Simulated scRNA-seq dataset — sc_example","text":"","code":"# Simulation library(\"splatter\") # Version 1.2.1  sim <- splatSimulate(batchCells = 200, nGenes = 10000,                      group.prob = c(0.4, 0.2, 0.2, 0.15, 0.05),                      de.prob = c(0.1, 0.2, 0.05, 0.1, 0.05),                      method = \"groups\", seed = 1) sim_counts <- counts(sim)[1:1000, ]  # SC3 Clustering library(\"SC3\") # Version 1.7.6 library(\"scater\") # Version 1.6.2  sim_sc3 <- SingleCellExperiment(assays = list(counts = sim_counts)) rowData(sim_sc3)$feature_symbol <- rownames(sim_counts) sim_sc3 <- normalise(sim_sc3) sim_sc3 <- sc3(sim_sc3, ks = 1:8, biology = FALSE, n_cores = 1) sim_sc3 <- runTSNE(sim_sc3)  # Seurat Clustering library(\"Seurat\") # Version 2.2.0  sim_seurat <- CreateSeuratObject(sim_counts) sim_seurat <- NormalizeData(sim_seurat, display.progress = FALSE) sim_seurat <- FindVariableGenes(sim_seurat, do.plot = FALSE,                                 display.progress = FALSE) sim_seurat <- ScaleData(sim_seurat, display.progress = FALSE) sim_seurat <- RunPCA(sim_seurat, do.print = FALSE) sim_seurat <- FindClusters(sim_seurat, dims.use = 1:6,                            resolution = seq(0, 1, 0.1),                            print.output = FALSE)  sc_example <- list(counts = counts(sim_sc3),                    logcounts = logcounts(sim_sc3),                    tsne = reducedDim(sim_sc3),                    sc3_clusters = as.data.frame(colData(sim_sc3)),                    seurat_clusters = sim_seurat@meta.data)"},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Store node aesthetics — store_node_aes","title":"Store node aesthetics — store_node_aes","text":"Store names node attributes use aesthetics graph attributes","code":""},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Store node aesthetics — store_node_aes","text":"","code":"store_node_aes(graph, node_aes_list, metadata)"},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Store node aesthetics — store_node_aes","text":"graph graph store attributes node_aes_list nested list containing node aesthetics metadata data.frame containing metadata can used aesthetics","code":""},{"path":"https://lazappi.github.io/clustree/reference/store_node_aes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Store node aesthetics — store_node_aes","text":"graph additional attributes","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-051-2023-11-05","dir":"Changelog","previous_headings":"","what":"clustree 0.5.1 (2023-11-05)","title":"clustree 0.5.1 (2023-11-05)","text":"CRAN release: 2023-11-05 Minor updates compatibility Seurat >= 5.0.0 ggplot2 >= 3.4.0","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-5-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.5.0.9001 (2023-10-24)","title":"clustree 0.5.1 (2023-11-05)","text":"Avoid warnings due deprecated functionality ggplot2 tidyselect. Includes increasing ggplot2 requirement >= 3.4.0. (Fixes #35)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-5-1-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.5.0.9000 (2023-10-24)","title":"clustree 0.5.1 (2023-11-05)","text":"Minor updates compatibility upcoming Seurat v5 release (Fixes #93)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-050-2022-06-24","dir":"Changelog","previous_headings":"","what":"clustree 0.5.0 (2022-06-24)","title":"clustree 0.5.0 (2022-06-24)","text":"CRAN release: 2022-06-25","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"minor-changes-0-5-0","dir":"Changelog","previous_headings":"","what":"Minor changes","title":"clustree 0.5.0 (2022-06-24)","text":"Add node_text_angle argument clustree() (Fixes #79, PR #80)","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-5-0","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.4.9001 (2022-06-24)","title":"clustree 0.5.0 (2022-06-24)","text":"Add node_text_angle argument clustree() (Fixes #79, PR #80)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-044-2021-11-06","dir":"Changelog","previous_headings":"","what":"clustree 0.4.4 (2021-11-06)","title":"clustree 0.4.4 (2021-11-06)","text":"CRAN release: 2021-11-08","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-4-4","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.4.4 (2021-11-06)","text":"Minor changes tests failing due changes Bioconductor 3.14 release Minor updates URLs documentation","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-043-2020-06-12","dir":"Changelog","previous_headings":"","what":"clustree 0.4.3 (2020-06-12)","title":"clustree 0.4.3 (2020-06-12)","text":"CRAN release: 2020-06-14","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-4-3","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.4.3 (2020-06-12)","text":"Fix axis label order clustree() (Fixes #44) Add checks handle features including “-” characters Seurat SingleCellExperiment interfaces clustree() clustree_overlay() (Fixes #43) Change metadata columns extracted compatibility tibble objects (Fixes #52)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"other-changes-0-4-3","dir":"Changelog","previous_headings":"","what":"Other changes","title":"clustree 0.4.3 (2020-06-12)","text":"Replace iris_clusts dataset nba_clusts dataset Increase R dependency > 3.5","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9003 (2020-06-12)","title":"clustree 0.4.3 (2020-06-12)","text":"Change metadata columns extracted compatibility tibble objects (Fixes #52)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9002 (2020-06-12)","title":"clustree 0.4.3 (2020-06-12)","text":"Replace iris_clusts dataset nba_clusts dataset","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3-2","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9001 (2020-03-20)","title":"clustree 0.4.3 (2020-06-12)","text":"Add checks handle features including “-” characters Seurat SingleCellExperiment interfaces clustree() clustree_overlay() (Fixes #43)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-3-3","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.2.9000 (2020-03-19)","title":"clustree 0.4.3 (2020-06-12)","text":"Fix axis label order clustree() (Fixes #44)","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-042-2020-01-29","dir":"Changelog","previous_headings":"","what":"clustree 0.4.2 (2020-01-29)","title":"clustree 0.4.2 (2020-01-29)","text":"CRAN release: 2020-01-29","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"bug-fixes-0-4-2","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"clustree 0.4.2 (2020-01-29)","text":"sc_example contained DataFrame rather data.frame SC3 data, now fixed Alpha now represent in_prop values 0 1 Change point colour resolution name determined side plots clustree_overlay() (Fixes #38) Fix missing alpha scale clustree() (Fixes #32) allow matching start column names without wildcard problem Issue #19 Fixes minor bugs discovered new unit tests","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"other-changes-0-4-2","dir":"Changelog","previous_headings":"","what":"Other changes","title":"clustree 0.4.2 (2020-01-29)","text":"Tests matching prefix values Test point colour clustree_overlay() rounded resolutions","code":""},{"path":[]},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9005 (2020-01-29)","title":"clustree 0.4.2 (2020-01-29)","text":"Add additional unit tests, including missing clustree_overlay() Minor fixes bugs discovered new tests","code":""},{"path":"https://lazappi.github.io/clustree/news/index.html","id":"clustree-0-4-2-1","dir":"Changelog","previous_headings":"Development versions","what":"clustree 0.4.1.9004 (2020-01-28)","title":"clustree 0.4.2 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