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author | ebi-gxa |
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date | Sat, 02 Mar 2024 10:42:01 +0000 |
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<tool id="seurat_find_markers" name="Seurat FindMarkers" profile="18.01" version="@SEURAT_VERSION@+galaxy0"> <description>find markers (differentially expressed genes)</description> <macros> <import>seurat_macros.xml</import> </macros> <expand macro="requirements" /> <expand macro="version" /> <command detect_errors="exit_code"><![CDATA[ seurat-find-markers.R @INPUT_OBJECT@ --output-text-file output.txt #if $genes_use: --genes-use '$genes_use' #end if #if str($logfc_threshold): --logfc-threshold '$logfc_threshold' #end if #if str($adv.min_pct): --min-pct '$adv.min_pct' #end if #if str($adv.min_diff_pct): --min-diff-pct '$adv.min_diff_pct' #end if #if $adv.only_pos: --only-pos '$adv.only_pos' #end if --test-use '$adv.test_use' #if str($max_cells_per_ident): --max-cells-per-ident '$max_cells_per_ident' #end if #if str($min_cells_per_gene): --min-cells-gene '$min_cells_per_gene' #end if #if str($min_cells_group): --min-cells-group '$min_cells_group' #end if ]]></command> <inputs> <expand macro="input_object_params"/> <expand macro="genes-use-input"/> <param name="logfc_threshold" label="LogFC logfc_threshold" optional="true" argument="--logfc-threshold" type="float" help="Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is 0.25 Increasing logfc.threshold speeds up the function, but can miss weaker signals."/> <param name="max_cells_per_ident" label="Max cells per ident" optional="true" argument="--max-cells-per-ident" type="integer" help="Down sample each identity class to a max number. Default is no downsampling. Not activated by default (set to Inf)."/> <param name="min_cells_per_gene" label="Min cells per gene" optional="true" argument="--min-cells-gene" type="integer" help="Minimum number of cells expressing the gene in at least one of the two groups, currently only used for poisson and negative binomial tests."/> <param name="min_cells_group" label="Min cells in one of the groups" optional="true" argument="--min-cells-group" type="integer"/> <section name="adv" title="Advanced Options"> <param name="min_pct" type="float" label="Min Pct" optional="true" help="Only test genes that are detected in a minimum fraction of min.pct cells in either of the two populations. Meant to speed up the function by not testing genes that are very infrequently expressed. Default is 0.1."/> <param name="min_diff_pct" type="float" label="Min diff Pct" optional="true" help="Only test genes that show a minimum difference in the fraction of detection between the two groups. Set to -Inf by default."/> <param name="only_pos" type="boolean" label="Only positive markers" truevalue="TRUE" falsevalue="" help="Only return positive markers (FALSE by default)."/> <param name="test_use" type="select" label="Test to use" help=""> <option value="wilcox" selected="true">Wilcoxon</option> <option value="bimod">Bi-modal</option> <option value="roc">ROC</option> <option value="t">t-Test</option> <option value="tobit">tobit</option> <option value="poisson">Poisson</option> <option value="negbinom">Negative binomia</option> <option value="MAST">MAST</option> <option value="DESeq2">DESeq2</option> </param> </section> </inputs> <outputs> <data name="output" format="csv" from_work_dir="output.txt" label="${tool.name} on ${on_string}: Text file"/> </outputs> <tests> <test> <param name="rds_seurat_file" ftype="rdata" value="E-MTAB-6077-3k_features_90_cells-clusters.rds"/> <output name="output" > <assert_contents> <has_n_lines n="1130" /> </assert_contents> </output> </test> </tests> <help><![CDATA[ .. class:: infomark **What it does** This tool finds markers (differentially expressed genes) for each of the identity classes in a dataset. It outputs a text file containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.) p-value adjustment is performed using bonferroni correction based on the total number of genes in the dataset. Other correction methods are not recommended, as Seurat pre-filters genes using the arguments above, reducing the number of tests performed. Lastly, as Aaron Lun has pointed out, p-values should be interpreted cautiously, as the genes used for clustering are the same genes tested for differential expression. @SEURAT_INTRO@ ----- **Inputs** * RDS object ----- **Outputs** * Text file .. _Seurat: https://www.nature.com/articles/nbt.4096 .. _Satija Lab: https://satijalab.org/seurat/ @VERSION_HISTORY@ ]]></help> <expand macro="citations" /> </tool>