Mercurial > repos > ebi-gxa > seurat_find_variable_genes

annotate seurat_find_variable_genes.xml @ 0:a56efad05337 draft

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planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
author ebi-gxa
date Wed, 03 Apr 2019 11:17:53 -0400
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a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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1 <tool id="seurat_find_variable_genes" name="Seurat FindVariableGenes" version="2.3.1+galaxy1">
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2 <description>identify variable 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-find-variable-genes.R
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10
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11 --input-object-file '$input'
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12 #if $mean:
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13 --mean-function '$mean'
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14 #end if
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15 #if $disp:
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16 --dispersion-function $disp
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17 #end if
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18 #if $xlow:
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19 --x-low-cutoff $xlow
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20 #end if
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21 #if $xhigh:
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22 --x-high-cutoff $xhigh
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23 #end if
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24 #if $ylow:
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25 --y-low-cutoff $ylow
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26 #end if
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27 #if $yhigh:
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28 --y-high-cutoff $yhigh
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29 #end if
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30 --output-object-file '$output'
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31 --output-text-file '$output_tab'
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32 ]]></command>
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33
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34 <inputs>
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35 <param name="input" argument="--input-object-file" type="data" format="rdata" label="Seurat RDS object" help="R serialized object for Seurat, normally the one produced by Seurat FindVariableGenes" />
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36 <param name="mean" argument="--mean-function" type="text" optional="True" label="Mean function" help="Function to compute x-axis value (average expression). Default is to take the mean of the detected (i.e. non-zero) values."/>
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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37 <param name="disp" argument="--dispersion-function" type="text" optional="True" label="Dispersion function" help="Function to compute y-axis value (dispersion). Default is to take the standard deviation of all values." />
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38 <param name="xlow" argument="--x-low-cutoff" type="float" optional="True" label="X-axis low cutoff" help="Bottom cutoff on x-axis for identifying variable genes."/>
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39 <param name="xhigh" argument="--x-high-cutoff" type="float" optional="True" label="X-axis high cutoff" help="Top cutoff on x-axis for identifying variable genes."/>
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40 <param name="ylow" argument="--y-low-cutoff" type="float" optional="True" label="Y-axis low cutoff" help="Bottom cutoff on y-axis for identifying variable genes."/>
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41 <param name="yhigh" argument="--y-high-cutoff" type="float" optional="True" label="Y-axis high cutoff" help="Top cutoff on y-axis for identifying variable genes."/>
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42 </inputs>
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43
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44 <outputs>
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45 <data name="output" format="rdata" from_work_dir="*.rds" label="${tool.name} on ${on_string}: Seurat RDS"/>
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46 <data name="output_tab" format="tabular" from_work_dir="*.tab" label="${tool.name} on ${on_string}: Variable genes tabular file"/>
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47 </outputs>
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48
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49 <tests>
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50 <test>
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51 <param name="input" ftype="rdata" value="out_norm.rds"/>
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52 <output name="output" ftype="rdata" value="out_findvar.rds" compare="sim_size"/>
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53 </test>
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54 </tests>
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55 <help><![CDATA[
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56 .. class:: infomark
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57
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58 **What it does**
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59
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60 Seurat_ is a toolkit for quality control, analysis, and exploration of single cell RNA sequencing data.
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61 It is developed and maintained by the `Satija Lab`_ at NYGC. Seurat aims to enable users to identify and
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62 interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse
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63 types of single cell data.
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64
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65 This tool identifies genes that are outliers on a 'mean variability plot'. First, uses
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66 a function to calculate average expression (mean.function) and dispersion (dispersion.function)
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67 for each gene. Next, divides genes into num.bin (deafult 20) bins based on
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68 their average expression, and calculates z-scores for dispersion within each
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69 bin. The purpose of this is to identify variable genes while controlling for
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70 the strong relationship between variability and average expression.
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71
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72 Exact parameter settings may vary empirically from dataset to dataset, and
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73 based on visual inspection of the plot.
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74
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75 Setting the y.cutoff parameter to 2 identifies genes that are more than two standard
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76 deviations away from the average dispersion within a bin. The default X-axis function
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77 is the mean expression level, and for Y-axis it is the log(Variance/mean). All mean/variance
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78 calculations are not performed in log-space, but the results are reported in log-space -
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79 see relevant functions for exact details.
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80
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81 -----
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82
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83 **Inputs**
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84
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85 * Seurat RDS object
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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86 * Mean function. Function to compute x-axis value (average expression). Default is to take the mean of the detected (i.e. non-zero) values.
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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87 * Dispersion function. Function to compute y-axis value (dispersion). Default is to take the standard deviation of all values.
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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88 * Bottom cutoff on x-axis for identifying variable genes.
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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89 * Top cutoff on x-axis for identifying variable genes.
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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90 * Bottom cutoff on y-axis for identifying variable genes.
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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91 * Top cutoff on y-axis for identifying variable genes.
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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93 -----
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95 **Outputs**
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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97 * Seurat RDS object. Places variable genes in object@var.genes. The result of all analysis is stored in object@hvg.info
a56efad05337 planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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98 * Tabular file of variable genes
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99
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100 .. _Seurat: https://www.nature.com/articles/nbt.4096
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101 .. _Satija Lab: https://satijalab.org/seurat/
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102
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103 @VERSION_HISTORY@
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104 ]]></help>
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105 <expand macro="citations" />
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106 </tool>