Mercurial > repos > ebi-gxa > scanpy_find_variable_genes

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"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 2db9e8cecb8d373874318e53ec2d4d7a64dd1b24-dirty"
author ebi-gxa
date Fri, 11 Sep 2020 11:06:13 +0000
parents f952b39f0794
children 79da59a0b180
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1 <?xml version="1.0" encoding="utf-8"?>
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2 <tool id="scanpy_find_variable_genes" name="Scanpy FindVariableGenes" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
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3 <description>based on normalised dispersion of expression</description>
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4 <macros>
1
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5 <import>scanpy_macros2.xml</import>
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6 </macros>
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7 <expand macro="requirements"/>
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8 <command detect_errors="exit_code"><![CDATA[
305d0cbe0ffd planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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9 ln -s '${input_obj_file}' input.h5 &&
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10 PYTHONIOENCODING=utf-8 scanpy-find-variable-genes
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11 --flavor '${flavor}'
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12 #if $min_mean
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13 --mean-limits ${min_mean} ${max_mean}
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14 #end if
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15 #if $min_disp
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16 --disp-limits ${min_disp} ${max_disp}
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17 #end if
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18 #if $n_top_gene
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19 --n-top-genes ${n_top_gene}
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20 #end if
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21 #if $span
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22 --span ${span}
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23 #end if
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24 --n-bins '${n_bin}'
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25 ${filter}
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26 @INPUT_OPTS@
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27 @OUTPUT_OPTS@
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28 ]]></command>
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29
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30 <inputs>
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31 <expand macro="input_object_params"/>
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32 <expand macro="output_object_params"/>
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33 <param name="flavor" argument="--flavor" type="select" label="Flavor of computing normalised dispersion">
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34 <option value="seurat" selected="true">Seurat</option>
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35 <option value="cell_ranger">Cell-ranger</option>
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36 <option value="seurat_v3" selected="true">Seurat V3</option>
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37 </param>
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38 <param name="min_mean" argument="--min-mean" type="float" min="0" value="0.0125" optional="true"
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39 label="Min value for normalised mean expression (in log1p scale), ignored if flavor='seurat_v3'"/>
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40 <param name="max_mean" argument="--max-mean" type="float" min="0" value="3" optional="true"
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41 label="Max value for normalised mean expresssion (in log1p scale), Ignored if flavor='seurat_v3'"/>
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42 <param name="min_disp" argument="--min-disp" type="float" min="0" value="0.5" optional="true"
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43 label="Min value for dispersion of expression, ignored if flavor='seurat_v3'"/>
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44 <param name="max_disp" argument="--max-disp" type="float" min="0" value="50" optional="true"
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45 label="Max value for dispersion of expresssion, ignored if flavor='seurat_v3'"/>
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46 <param name="n_top_gene" argument="--n-top-genes" type="integer" value="2000" optional="true"
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47 label="Number of top variable genes to keep, mandatory if flavor='seurat_v3'"/>
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48 <param name="span" argument="--span" type="float" min="0" max="1" value="0.3" optional="true"
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49 label="The fraction of the data (cells) used when estimating the variance in the loess model fit if flavor='seurat_v3'"/>
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50 <param name="n_bin" argument="--n-bins" type="integer" value="20" label="Number of bins for binning the mean expression"/>
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51 <param name="filter" argument="--subset" type="boolean" truevalue="--subset" falsevalue="" checked="false"
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52 label="Remove genes not marked as highly variable" help="When set, inplace subset to highly-variable genes, otherwise only flag highly-variable genes."/>
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53 <param name="batch_key" argument="--batch-key" type="text" label="Batch key" help="If specified, highly-variable genes are selected within each batch separately and merged. This simple process avoids the selection of batch-specific genes and acts as a lightweight batch correction method. For all flavors, genes are first sorted by how many batches they are a HVG. For dispersion-based flavors ties are broken by normalized dispersion. If flavor = 'seurat_v3', ties are broken by the median (across batches) rank based on within-batch normalized variance."/>
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54 </inputs>
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55
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56 <outputs>
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57 <expand macro="output_data_obj" description="Variable genes"/>
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58 </outputs>
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60 <tests>
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61 <test>
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62 <param name="input_obj_file" value="normalise_data.h5"/>
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63 <param name="input_format" value="anndata"/>
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64 <param name="output_format" value="anndata"/>
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65 <param name="flavor" value="seurat"/>
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66 <param name="n_bin" value="20"/>
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67 <param name="min_mean" value="0.0125"/>
b089f4a55e6b "planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"
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68 <param name="max_mean" value="3"/>
b089f4a55e6b "planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"
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69 <param name="min_disp" value="0.5"/>
b089f4a55e6b "planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"
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70 <param name="max_disp" value="1e9"/>
0
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71 <output name="output_h5" file="find_variable_genes.h5" ftype="h5" compare="sim_size"/>
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72 </test>
305d0cbe0ffd planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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73 </tests>
305d0cbe0ffd planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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74
305d0cbe0ffd planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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75 <help><![CDATA[
1
b089f4a55e6b "planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"
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76 ==============================================================
b089f4a55e6b "planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"
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77 Mark highly variable genes (`scanpy.pp.highly_variable_genes`)
b089f4a55e6b "planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"
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78 ==============================================================
0
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79
1
b089f4a55e6b "planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"
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80 Depending on `flavor`, this reproduces the R-implementations of Seurat or Cell Ranger.
0
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81
305d0cbe0ffd planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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82 The normalized dispersion is obtained by scaling with the mean and standard
305d0cbe0ffd planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4
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83 deviation of the dispersions for genes falling into a given bin for mean
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84 expression of genes. This means that for each bin of mean expression, highly
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85 variable genes are selected.
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86
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87 @HELP@
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88
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89 @VERSION_HISTORY@
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90 ]]></help>
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91 <expand macro="citations">
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92 <citation type="doi">10.1038/nbt.3192</citation>
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93 <citation type="doi">10.1038/ncomms14049</citation>
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94 </expand>
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95 </tool>