Mercurial > repos > ebi-gxa > decoupler_pathway_inference
diff decoupler_pathway_inference.xml @ 0:77d680b36e23 draft
planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 1034a450c97dcbb77871050cf0c6d3da90dac823
| author | ebi-gxa |
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| date | Fri, 15 Mar 2024 12:17:49 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/decoupler_pathway_inference.xml Fri Mar 15 12:17:49 2024 +0000 @@ -0,0 +1,129 @@ +<tool id="decoupler_pathway_inference" name="Decoupler Pathway Inference" version="1.4.0+galaxy0" profile="20.05" license="MIT"> + <description> + of functional genesets/pathways for scRNA-seq data. + </description> + <requirements> + <requirement type="package" version="1.4.0">decoupler</requirement> + </requirements> + <command> + python '$__tool_directory__/decoupler_pathway_inference.py' + -i '$input_anndata' + -n '$input_network_file' + --min_n "$min_n" + --method '$method' + $use_raw + --source $source + --target $target + --weight $weight + --output "inference" + $write_activities_path + </command> + <inputs> + <param name="input_anndata" type="data" format="h5ad" label="Input AnnData file" /> + <param name="input_network_file" type="data" format="tabular" label="Input Network file" help="Tabular file with columns Source, Target and Weight. A source gene/pathway regulates/contains a target gene, weights can be either positive or negative. The source element needs to be part of the network, the target is a gene in the network and in the dataset" /> + <param name="min_n" type="integer" min="0" value="5" label="Minimum targets per source." help="If targets are less than minimum, sources are removed" /> + <param name="method" type="select" label="Activity inference method"> + <option value="mlm" selected="true">Multivariate linear model (MLM)</option> + <option value="ulm">Univariate linear model (ULM)</option> + </param> + <param name="use_raw" type="boolean" truevalue="--use_raw" falsevalue="" checked="false" label="Use the raw part of the AnnData object" /> + <param name="write_activities_path" type="boolean" truevalue="--activities_path anndata_activities_path.h5ad" falsevalue="" checked="true" label="Write the activities AnnData object (contains the MLM/ULM activity results for each pathway and each cell in the main matrix, it is not a replacement of the original AnnData provided as input)." /> + <param name="source" type="text" value='source' label="Column name in network with source nodes." help="If empty then default is 'source' is used." /> + <param name="target" type="text" value='target' label="Column name in network with target nodes." help="If empty then default is 'target' is used." /> + <param name="weight" type="text" value='weight' label="Column name in network with weight." help="If empty then default is 'weight' is used." /> + </inputs> + <outputs> + <data name="output_ad" format="h5ad" from_work_dir="anndata_activities_path.h5ad" label="${tool.name} on ${on_string}: Regulators/Pathways activity AnnData file"> + <filter>write_activities_path</filter> + </data> + <data name="output_table" format="tabular" from_work_dir="inference.tsv" label="${tool.name} on ${on_string}: Output estimate table" /> + </outputs> + <tests> + <!-- Hint: You can use [ctrl+alt+t] after defining the inputs/outputs to auto-scaffold some basic test cases. --> + + <test expect_num_outputs="2"> + <param name="input_anndata" value="pbmc3k_processed.h5ad"/> + <param name="input_network_file" value="progeny_test.tsv"/> + <param name="min_n" value="0"/> + <param name="method" value="mlm"/> + <param name="use_raw" value="false"/> + <param name="write_activities_path" value="true"/> + <param name="source" value="source"/> + <param name="target" value="target"/> + <param name="weight" value="weight"/> + <output name="output_ad"> + <assert_contents> + <has_h5_keys keys="obsm/mlm_estimate"/> + </assert_contents> + </output> + <output name="output_table"> + <assert_contents> + <has_n_columns n="5"/> + </assert_contents> + </output> + </test> + <test> + <param name="input_anndata" value="pbmc3k_processed.h5ad"/> + <param name="input_network_file" value="progeny_test_2.tsv"/> + <param name="min_n" value="0"/> + <param name="method" value="ulm"/> + <param name="use_raw" value="false"/> + <param name="write_activities_path" value="true"/> + <param name="source" value="source"/> + <param name="target" value="target"/> + <param name="weight" value="weight"/> + <output name="output_ad"> + <assert_contents> + <has_h5_keys keys="obsm/ulm_estimate"/> + </assert_contents> + </output> + <output name="output_table"> + <assert_contents> + <has_n_columns n="5"/> + </assert_contents> + </output> + </test> + </tests> + <help> +**What it does** + +Usage +..... + + +**Description** + +This tool extracts pathway activity inference using decoupler. + +**Input** + +The input file should be an AnnData object in H5AD format. The tool accepts an H5AD file containing raw or normalized data. + +The tool also takes network file containing a collection of pathways and their target genes, with weights for each interaction. + Example: + ``` + source target weight + 0 T1 G01 1.0 + 1 T1 G02 1.0 + 2 T1 G03 0.7 + 3 T2 G04 1.0 + 4 T2 G06 -0.5 + ``` + +You can also specify whether to use the raw data in the AnnData object instead of the X matrix using the "use_raw" parameter and Minimum of targets per source using "min_n". + + +**Output** + +The tool outputs an AnnData object containing the scores in the "obs" field, and tab-separated text files containing the scores for each cell. + +If the "write_activities_path" parameter is set to "true", the tool will write the modified AnnData object to an H5AD file. +If the "write_inference" parameter is set to "true", the tool will output a tab-separated text file containing the scores for each cell. + + + + </help> + <citations> + <citation type="doi">10.1093/bioadv/vbac016 </citation> + </citations> +</tool>