Mercurial > repos > ebi-gxa > seurat_scale_data

annotate seurat_scale_data.xml @ 1:7ef152a02e71 draft

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planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 0a95e950ac73efdc9e84025ecb547e66fc3b83f6
author ebi-gxa
date Wed, 13 Mar 2019 12:52:17 -0400
parents 2890cec5229f
children 52ccdd3fb5e8
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1 <tool id="seurat_scale_data" name="Seurat ScaleData" version="2.3.1+galaxy1">
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2 <description>scale and center genes</description>
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3 <macros>
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4 <import>seurat_macros.xml</import>
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5 </macros>
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6 <expand macro="requirements" />
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7 <expand macro="version" />
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8 <command detect_errors="exit_code"><![CDATA[
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9 seurat-scale-data.R
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11 --input-object-file '$input'
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12 #if $vars:
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13 --vars-to-regress '$vars'
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14 #else
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15 --vars-to-regress nUMI
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16 #end if
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18 #if $genes:
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19 --genes-use '$genes'
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20 #end if
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22 --model-use '$model'
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24 $use_umi
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25 $do_center
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27 #if $scale_max:
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28 --scale-max '$scale_max'
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29 #end if
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30
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31 #if $block_size:
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32 --block-size '$block_size'
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33 #end if
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34
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35 #if $min_cells_to_block:
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36 --min-cells-to-block '$min_cells_to_block'
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37 #end if
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38
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39 $check_for_norm
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42
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43 --output-object-file '$output'
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44 ]]></command>
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45
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46 <inputs>
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47 <param name="input" argument="--input-object-file" type='data' format='rdata' help="File name in where a serialized R matrix object can be found." label="Seurat RDS object"/>
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48 <param name="genes" argument="--genes-use" type='data' format='txt' optional='true' help="File to be used to derive a vector of gene names to scale/center (one gene per line). Default is all genes in object@data."/>
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49 <param name="vars" argument="--vars-to-regress" type='text' optional='True' label="Vars to regress" help="Comma-separated list of variables to regress out (previously latent.vars in RegressOut). For example, nUMI, or percent.mito."/>
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50 <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.">
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51 <option value="linear" selected="true">Linear model</option>
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52 <option value="poisson">Poisson model</option>
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53 <option value="negbinom">Negative binomial model</option>
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54 </param>
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55 <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'."/>
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56 <param name="do_center" argument="--do-center" type="boolean" falsevalue="--do-center FALSE" truevalue="" checked="true" label="Perform centering" help="Whether to center the data."/>
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57 <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."/>
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58 <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."/>
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59 <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."/>
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60 <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."/>
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61 </inputs>
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62
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63 <outputs>
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64 <data name="output" format="rdata" from_work_dir="*.rds" label="${tool.name} on ${on_string}: Seurat RDS"/>
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65 </outputs>
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66
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67 <tests>
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68 <test>
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69 <param name="input" ftype="rdata" value="out_findvar.rds"/>
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70 <output name="output" ftype="rdata" value="out_scale.rds" compare="sim_size"/>
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71 </test>
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72 </tests>
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73 <help><![CDATA[
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74 .. class:: infomark
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75
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76 **What it does**
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77
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78 Seurat_ is a toolkit for quality control, analysis, and exploration of single cell RNA sequencing data.
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79 It is developed and maintained by the `Satija Lab`_ at NYGC. Seurat aims to enable users to identify and
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80 interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse
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81 types of single cell data.
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82
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83 This tool regresses out variables in a Seurat object to mitigate the effect of confounding factors.
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84
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85
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86 -----
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87
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88 **Inputs**
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89
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90 * Seurat RDS object, probably normalised.
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91 * 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.
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92 * Variables to regress
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93 * Statistical model to use.
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94 * Use UMIs (boolean)
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95 * Do centering (boolean)
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96 * Scale maximum
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97 * Block size
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98 * Minimum number of cells to block
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99 * Check that data is normalised
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100
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101 -----
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102
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103 **Outputs**
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104
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105 * Seurat RDS object, scaled.
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106
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107 .. _Seurat: https://www.nature.com/articles/nbt.4096
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108 .. _Satija Lab: https://satijalab.org/seurat/
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109
1
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110 @VERSION_HISTORY@
0
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111 ]]></help>
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112 <expand macro="citations" />
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113 </tool>