giulio.benedetti@utu.fi -
28 October 2024
+1 November 2024
- Source:vignettes/miaDash.Rmd
+ Source: vignettes/miaDash.Rmd
miaDash.Rmd28 October 2024
Introduction
+This notebook provides a practical introduction to the Microbiome +Analysis Dashboard (miaDash), an interactive app to analyse and explore +microbiome data. Feel free to try it online at this address with your +data or one of the ready-to-use example datasets. Here, its usage and +functionality are described in more detail.
Motivation
+Most of the tools available for microbiome data analysis require some +knowledge of programming. This represents a burden for practitioners +more interested in getting results than learning how to program. To this +end, miaDash aims to make microbiome analysis accessible to anyone who +needs it, with or without any computational skills.
+As a word of caution, while the app removes the burden of +programming, it is still critical to understand the nature of microbiome +data and how it can be analysed. Such knowledge can be acquired from the +online book Orchestrating +Microbiome Analysis (OMA) and several other independent resources. +The following section presents what is currently possible in the +app.
Interface
+The interface is divided into five tabs that reflect the steps of a +typical microbiome analysis pipeline. First, the dataset of interest can +be uploaded through the Import tab, where several data types and file +formats are supported. Alternatively, one of the available example +datasets can be used for practice. Second, a set of operations can be +applied to the dataset through the Manipulate tab, which include methods +for subsetting features by prevalence, agglomerating by taxonomic level +and transforming assays. Third, the dataset can be analysed through the +Estimate tab, which provide common techniques to quantify alpha and beta +diversity. Finally, results can be explored through the Visualise tab, +where an interactive explorer can be launched with a customisable set of +panels that illustrate different aspects of the data.
Tutorial
+The app can be used online or locally, depending on resource +availability and size of the dataset to analyse. In general, the online +version is freely available, so that data of any type can be tested +there. However, running the app locally might be a better option for +larger datasets (> 1000 features). In this case, you may also +consider subsetting and/or agglomerating the data.
Installation
+If you decided to run the app locally, make sure to have R installed +in your machine and execute the following command:
-remotes::install_github("RiboRings/miaDash")# Install from GitHub
+remotes::install_github("RiboRings/miaDash")Once the package is successfully installed, you should have access to +the development version of miaDash.
Example
+This section shows how to get started with miaDash. If you are using +it locally, run the next code chunk to launch the app. Otherwise, you +can skip it.
-library(miaDash)
+# Import miaDash
+library(miaDash)
+# Instantiate app
app <- miaDash()
# Launch miaDash
if (interactive()) {
shiny::runApp(app)
}
As described in Section 1.2, The dashboard +consists of five different windows with tools to import, manipulate, +analyse and visualise the dataset of choice. After launching the app, it +appears as follows:
+
At first, the variety of options might feel intimidating, so you can +click on the question mark on the top right to receive a short tour of +the windows available in the app.
+Once the dataset was imported and analysed according to your +objective, you can choose which visualisations to use from the Visualise +window and press the button “Launch iSEEtree” to create and customise +the plots. After adjusting the parameters of the different panels, the +app might look something like this:
+
As before, you can click on the question mark on the top right to +receive a tour of the panels and their parameters. The best way to get +familiar with the interface is to experiment with the parameters below +each panel.
Citation
Background Knowledge
+miaDash originates from the joint effort of the R/Bioconductor
+community. It is mainly based on the following software:
+
+- R (R Core Team, 2024), statistical programming language
+-
+mia (Borman,
+Ernst, Shetty, and Lahti, 2024), framework for microbiome data
+analysis
+-
+iSEEtree
+(Benedetti and Lahti, 2024), TreeSummarizedExperiment interactive
+explorer
+-
+iSEE
+(Rue-Albrecht, Marini, Soneson, and Lun, 2018), SummarizedExperiment
+interactive explorer
+-
+TreeSummarizedExperiment
+(Huang, Soneson, Ernst, Rue-Albrecht, Yu, Hicks, and Robinson, 2021), S4
+container for hierarchical data
+-
+shiny (Chang,
+Cheng, Allaire, Sievert, Schloerke, Xie, Allen, McPherson, Dipert, and
+Borges, 2024), web app development in R
+
Help
+You can reach us by one of the communication channels listed here. +We are happy to receive questions, suggestions as well as contributions. +For the last point, check the contributor +guidelines.
References +
++[1] +G. Benedetti and L. Lahti. iSEEtree: Interactive visualisation for +microbiome data. R package version 0.99.8, commit +b034d1fc66308a0e51286ad0ab0a8ab65bee6fb5. 2024. URL: +https://github.com/microbiome/iSEEtree. +
++[2] +T. Borman, F. Ernst, S. Shetty, et al. mia: Microbiome +analysis. R package version 1.13.47. 2024. DOI: +10.18129/B9.bioc.mia. +URL: +https://bioconductor.org/packages/mia. +
++[3] +W. Chang, J. Cheng, J. Allaire, et al. shiny: Web Application +Framework for R. R package version 1.9.1, https://github.com/rstudio/shiny. 2024. URL: +https://shiny.posit.co/. +
++[4] +R. Huang, C. Soneson, F. G. Ernst, et al. “TreeSummarizedExperiment: a +S4 class for data with hierarchical structure”. In: +F1000Research 9 (2021), p. 1246. URL: +https://f1000research.com/articles/9-1246. +
++[5] +R Core Team. R: A Language and Environment for Statistical +Computing. R Foundation for Statistical Computing. Vienna, Austria, +2024. URL: +https://www.R-project.org/. +
++[6] +K. Rue-Albrecht, F. Marini, C. Soneson, et al. “iSEE: Interactive +SummarizedExperiment Explorer”. In: F1000Research 7 +(Jun. 2018), p. 741. DOI: +10.12688/f1000research.14966.1. +
Authors and Citation
Usage
-miaDash is available online at this address. While suitable for small and medium datasets, the online version may slow down when larger datasets are analysed (< 1000 features). In this case, the app can be installed and run locally. Either way, the app also provides functionality to subset and agglomerate the data.
+miaDash is available online at this address. While suitable for small and medium datasets, the online version may slow down when larger datasets are analysed (> 1000 features). In this case, the app can be installed and run locally. Either way, functionality to subset and agglomerate the data is also provided in the app.
Installation instructions
diff --git a/pkgdown.yml b/pkgdown.yml
index 0a8716e..d0fb05b 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -3,4 +3,4 @@ pkgdown: 2.1.1
pkgdown_sha: ~
articles:
miaDash: miaDash.html
-last_built: 2024-10-28T20:26Z
+last_built: 2024-11-01T18:10Z
diff --git a/reference/create_observers.html b/reference/create_observers.html
index c4fb0a8..3bd6c59 100644
--- a/reference/create_observers.html
+++ b/reference/create_observers.html
@@ -46,7 +46,7 @@
diff --git a/reference/landing_page.html b/reference/landing_page.html
index ff06db3..e7c4156 100644
--- a/reference/landing_page.html
+++ b/reference/landing_page.html
@@ -45,7 +45,7 @@
diff --git a/reference/miaDash.html b/reference/miaDash.html
index 7b8733a..b9af365 100644
--- a/reference/miaDash.html
+++ b/reference/miaDash.html
@@ -46,7 +46,7 @@
diff --git a/reference/render_output.html b/reference/render_output.html
index 1c27c45..0e78d59 100644
--- a/reference/render_output.html
+++ b/reference/render_output.html
@@ -46,7 +46,7 @@
diff --git a/reference/utils.html b/reference/utils.html
new file mode 100644
index 0000000..0d8a845
--- /dev/null
+++ b/reference/utils.html
@@ -0,0 +1,101 @@
+
+Utilities — utils • miaDash
+
+
+
+
+
+
+
+
+
+
+
+
+ Helper functions and constants to support the app functionality.
+
+
+
+ .import_datasets(selection)
+
+.print_message(...)
+
+.check_formula(form, se)
+
+.check_panel(se, panel_list, panel_class, panel_fun, wtext)
+
+default_panels
+
+other_panels
+
+.actionbutton_biocstyle
+
+
+
+ Format
+ An object of class character of length 7.
+An object of class character of length 5.
+An object of class character of length 1.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/sitemap.xml b/sitemap.xml
index 875da9a..15194b9 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -9,5 +9,6 @@
/reference/landing_page.html /reference/miaDash.html /reference/render_output.html /reference/utils.html
Helper functions and constants to support the app functionality.
+.import_datasets(selection)
+
+.print_message(...)
+
+.check_formula(form, se)
+
+.check_panel(se, panel_list, panel_class, panel_fun, wtext)
+
+default_panels
+
+other_panels
+
+.actionbutton_biocstyleFormat
+An object of class character of length 7.
An object of class character of length 5.
An object of class character of length 1.