initial import

.github/workflows/main.yml

@@ -44,11 +44,11 @@ jobs:
       with:
         directory: .test
         snakefile: workflow/Snakefile
-        args: "--use-conda --show-failed-logs --cores 3 --conda-cleanup-pkgs cache --all-temp"
+        args: "--sdm apptainer --show-failed-logs --cores 1 --all-temp"
 
     - name: Test report
       uses: snakemake/[email protected]
       with:
         directory: .test
         snakefile: workflow/Snakefile
-        args: "--report report.zip"
+        args: "--report report.zip"

.github/workflows/release-please.yml

@@ -14,4 +14,4 @@ jobs:
         id: release
         with:
           release-type: go # just keep a changelog, no version anywhere outside of git tags
-          package-name: <repo>
+          package-name: SPIMprep

.snakemake-workflow-catalog.yml

@@ -5,7 +5,7 @@ usage:
     desc: # describe your flags here in a few sentences (they will be inserted below the example commands)
     flags: # put your flags here
   software-stack-deployment: # definition of software deployment method (at least one of conda, singularity, or singularity+conda)
-    conda: true # whether pipeline works with --use-conda
-    singularity: false # whether pipeline works with --use-singularity
+    conda: false # whether pipeline works with --use-conda
+    singularity: true # whether pipeline works with --use-singularity
     singularity+conda: false # whether pipeline works with --use-singularity --use-conda
-  report: true # add this to confirm that the workflow allows to use 'snakemake --report report.zip' to generate a report containing all results and explanations
+  report: true # add this to confirm that the workflow allows to use 'snakemake --report report.zip' to generate a report containing all results and explanations

README.md

@@ -1,21 +1,13 @@
-# Snakemake workflow: `<name>`
+# Snakemake workflow: `SPIMprep`
 
 [![Snakemake](https://img.shields.io/badge/snakemake-≥6.3.0-brightgreen.svg)](https://snakemake.github.io)
 [![GitHub actions status](https://github.com/<owner>/<repo>/workflows/Tests/badge.svg?branch=main)](https://github.com/<owner>/<repo>/actions?query=branch%3Amain+workflow%3ATests)
 
-
-A Snakemake workflow for `<description>`
-
+A Snakemake workflow forp re-processing single plane illumination microscopy (SPIM, aka lightsheet microscopy)
 
 ## Usage
 
-The usage of this workflow is described in the [Snakemake Workflow Catalog](https://snakemake.github.io/snakemake-workflow-catalog/?usage=<owner>%2F<repo>).
-
-If you use this workflow in a paper, don't forget to give credits to the authors by citing the URL of this (original) <repo>sitory and its DOI (see above).
+The usage of this workflow is described in the [Snakemake Workflow Catalog](https://snakemake.github.io/snakemake-workflow-catalog/?usage=khanlab%2Fspimprep).
 
-# TODO
 
-* Replace `<owner>` and `<repo>` everywhere in the template (also under .github/workflows) with the correct `<repo>` name and owning user or organization.
-* Replace `<name>` with the workflow name (can be the same as `<repo>`).
-* Replace `<description>` with a description of what the workflow does.
-* The workflow will occur in the snakemake-workflow-catalog once it has been made public. Then the link under "Usage" will point to the usage instructions if `<owner>` and `<repo>` were correctly set.
+Note: Designed to work with data from the Miltenyi Biotec UltraMicroscope Blaze, but could be adapted to other types of data

config/README.md

@@ -1,2 +1 @@
-Describe how to configure the workflow (using config.yaml and maybe additional files).
-All of them need to be present with example entries inside of the config folder.
+Add datasets to datasets.tsv, and update config.yml to customize options.

config/config.yml

@@ -0,0 +1,74 @@
+datasets: 'config/datasets.tsv'
+
+
+root: 'results'
+work: 'work' 
+
+targets:
+  desc:
+    - stitchedflatcorr  #e.g. can be stitchedraw to skip flatfield correction
+
+import:
+  raw_tif_pattern: "{prefix}_Blaze[{tilex} x {tiley}]_C{channel}_xyz-Table Z{zslice}.ome.tif"
+  raw_tif_glob: "{prefix}_Blaze[[]{tilex} x {tiley}[]]_C{channel}_xyz-Table Z{zslice}.ome.tif"
+  intensity_rescaling: 0.5 #raw images seem to be at the upper end of uint16 (over-saturated) -- causes wrapping issues when adjusting with flatfield correction etc. this rescales the raw data as it imports it..
+
+
+
+basic_flatfield_corr:
+  max_n_images: 500
+  fitting_opts:
+    get_darkfield: True
+    smoothness_flatfield: 1.0
+    smoothness_darkfield: 1.0
+    sparse_cost_darkfield: 0.01
+
+
+bigstitcher:
+  calc_pairwise_shifts:
+    downsample_in_x: 4
+    downsample_in_y: 4
+    downsample_in_z: 1
+  filter_pairwise_shifts:
+    min_r: 0.7
+  fuse_dataset:
+    downsampling: 1
+    block_size_x: 1024 # for storage
+    block_size_y: 1024
+    block_size_z: 1
+    block_size_factor_x: 2 #e.g. 2 will use 2*block_size for computation
+    block_size_factor_y: 2
+    block_size_factor_z: 1
+
+ome_zarr:
+  max_downsampling_layers: 4 # e.g. 4 levels: { 0: orig, 1: ds2, 2: ds4, 3: ds8, 4: ds16}
+  rechunk_size: #z, y, x
+    - 1 
+    - 1024
+    - 1024
+  scaling_method: 'local_mean' #can be nearest, gaussian, local_mean, zoom (zoom uses spline interp)
+
+nifti:
+  levels: #cannot be higher than max_downsampling_layers in ome_zarr
+    - 3
+    - 4
+
+templates: 
+  - ABAv3
+
+atlases:
+  ABAv3:
+    anat: 'resources/ABAv3/P56_Atlas.nii.gz'
+    dseg: 'resources/ABAv3/P56_Annotation.nii.gz'
+    lut: 'resources/ABAv3/labelmapper_ABAv3_to_all.json'
+
+atlasreg:
+  stain: autof
+  level: 4
+  desc: stitchedflatcorr
+
+
+
+containers:
+  spimprep: 'docker://khanlab/spimprep-deps:main'
+  miracl: 'docker://mgoubran/miracl:2.2.5'

config/datasets.tsv

@@ -0,0 +1,2 @@
+subject	sample	acq	stain_0	stain_1	dataset_path
+mouse1	brain	1x	abeta	autof	input_data/test_lightsheet_ome.tar