Mercurial > repos > ebi-gxa > seurat_scale_data
view seurat_scale_data.xml @ 4:4147dc085d45 draft
"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit a1ad1ddd9b8e4db5bb82c3accae8311e0e488b19"
author | ebi-gxa |
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date | Fri, 27 Nov 2020 13:49:56 +0000 |
parents | 1a8e93921f01 |
children | d2f6eac0ad42 |
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<tool id="seurat_scale_data" name="Seurat ScaleData" version="@SEURAT_VERSION@+galaxy0"> <description>scale and center genes</description> <macros> <import>seurat_macros.xml</import> </macros> <expand macro="requirements" /> <expand macro="version" /> <command detect_errors="exit_code"><![CDATA[ seurat-scale-data.R @INPUT_OBJECT@ #if $vars: --vars-to-regress '$vars' #else --vars-to-regress nUMI #end if #if $genes_use: --genes-use '$genes_use' #end if --model-use '$model' $use_umi $do_not_center #if $scale_max: --scale-max '$scale_max' #end if #if $block_size: --block-size '$block_size' #end if #if $min_cells_to_block: --min-cells-to-block '$min_cells_to_block' #end if $check_for_norm @OUTPUT_OBJECT@ ]]></command> <inputs> <expand macro="input_object_params"/> <expand macro="output_object_params"/> <expand macro="genes-use-input"/> <param name="vars" argument="--vars-to-regress" type='text' value="nCount_RNA" label="Vars to regress" help="Comma-separated list of variables to regress out (previously latent.vars in RegressOut). For example, nCount_RNA, or percent.mito."> <validator type="regex" message="Please only use letters or numbers">^[\(\w\)]+$</validator> <option value="nCount_RNA">nCount_RNA</option> <option value="nFeature_RNA">nFeature_RNA</option> </param> <param name="model" argument="--model-use" type="select" label="Statistical model" help="Use a linear model or generalized linear model (poisson, negative binomial) for the regression."> <option value="linear" selected="true">Linear model</option> <option value="poisson">Poisson model</option> <option value="negbinom">Negative binomial model</option> </param> <param name="use_umi" argument="--use-umi" type="boolean" truevalue="--use-umi TRUE" falsevalue="" checked="false" label="Use UMIs." help="Regress on UMI count data. Default is FALSE for linear modeling, but automatically set to TRUE if model.use is 'negbinom' or 'poisson'."/> <param name="do_not_center" argument="--do-not-center" type="boolean" falsevalue="" truevalue="--do-not-center" checked="false" label="Skip centering" help="By default data is centered, with this option you can skip centering."/> <param name="do_not_scale" argument="--do-not-scale" type="boolean" falsevalue="" truevalue="--do-not-scale" checked="false" label="Skip scaling" help="By default data is scaled, with this option you can skip scaling."/> <param name="scale_max" argument="--scale-max" optional="true" type="float" label="Scale maximum" help = "Max value to return for scaled data. The default is 10. Setting this can help reduce the effects of genes that are only expressed in a very small number of cells. If regressing out latent variables and using a non-linear model, the default is 50."/> <param name="block_size" argument="--block-size" optional="true" type="integer" label="Block size" help = "Default size for number of genes to scale at in a single computation. Increasing block.size may speed up calculations but at an additional memory cost. Defaults to 1000 if not specified."/> <param name="min_cells_to_block" argument="--min-cells-to-block" optional="true" type="integer" label="Minimum number of cells to block" help="If object contains fewer than this number of cells, don't block for scaling calculations. Defaults to 1000."/> <param name="check_for_norm" argument="--check-for-norm" optional="true" type="boolean" falsevalue="--check-for-norm FALSE" truevalue="" label="Check that data is normalized" help="Check to see if data has been normalized, if not, output a warning (TRUE by default). Data can be normalised by Seurat normalise module."/> </inputs> <outputs> <expand macro="output_files"/> </outputs> <tests> <test> <param name="rds_seurat_file" ftype="rdata" value="variable_genes_seurat.rds"/> <param name="vars_to_regress" value="nCount_RNA" /> <param name="use_umi" value="True" /> <output name="rds_seurat_file" ftype="rdata" value="scaled_seurat.rds" compare="sim_size" delta="1000000000" /> </test> </tests> <help><![CDATA[ .. class:: infomark **What it does** This tool regresses out variables in a Seurat object to mitigate the effect of confounding factors. @SEURAT_INTRO@ ----- **Inputs** * Seurat RDS object, probably normalised. * Genes to use. A file with a vector of gene names to scale/center (one gene per line). Default is all genes in object@data. * Variables to regress * Statistical model to use. * Use UMIs (boolean) * Do centering (boolean) * Scale maximum * Block size * Minimum number of cells to block * Check that data is normalised ----- **Outputs** * Seurat RDS object, scaled. .. _Seurat: https://www.nature.com/articles/nbt.4096 .. _Satija Lab: https://satijalab.org/seurat/ @VERSION_HISTORY@ ]]></help> <expand macro="citations" /> </tool>