view scanpy-find-cluster.xml @ 0:ce27ae8a36cd draft

planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4
author ebi-gxa
date Wed, 03 Apr 2019 11:09:12 -0400
parents
children ee181563bae7
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<?xml version="1.0" encoding="utf-8"?>
<tool id="scanpy_find_cluster" name="Scanpy FindCluster" version="@TOOL_VERSION@+galaxy1">
  <description>based on community detection on KNN graph</description>
  <macros>
    <import>scanpy_macros.xml</import>
  </macros>
  <expand macro="requirements"/>
  <command detect_errors="exit_code"><![CDATA[
ln -s '${input_obj_file}' input.h5 &&
PYTHONIOENCODING=utf-8 scanpy-find-cluster.py
    -i input.h5
    -f '${input_format}'
    -o output.h5
    -F '${output_format}'
    #if $output_cluster
        --output-text-file output.tsv
    #end if
    #if $settings.default == "false"
        --flavor '${settings.flavor}'
        --key-added '${settings.key_added}'
        -s '${settings.random_seed}'
        #if $settings.flavor == "vtraag" and $settings.resolution_file
            --resolution \$( cat $settings.resolution_file )
        #elif $settings.flavor == "vtraag"
            --resolution '${settings.resolution}'
        #end if
        #if $settings.restrict_to
            --restrict-to '${settings.restrict_to}'
        #end if
        #if $settings.use_weights
            --use-weights
        #end if
    #end if
]]></command>

  <inputs>
    <expand macro="input_object_params"/>
    <expand macro="output_object_params"/>
    <param name="output_cluster" type="boolean" checked="true" label="Output cluster in two column text format"/>
    <conditional name="settings">
      <param name="default" type="boolean" checked="true" label="Use programme defaults"/>
      <when value="true"/>
      <when value="false">
        <param name="flavor" argument="--flavor" type="select" label="Use the indicated representation">
          <option value="vtraag" selected="true">vtraag</option>
          <option value="igraph">igraph</option>
        </param>
        <param name="resolution" argument="--resolution" type="float" value="1.0" label="Resolution, high value for more and smaller clusters"/>
        <param name="resolution_file" argument="--resolution" type="data" format="txt,tsv" optional="true" label="File with resolution, use with parameter iterator. Overrides the resolution setting"/>
        <param name="restrict_to" argument="--restrict-to" type="text" optional="true" label="Restrict clustering to certain sample categories"/>
        <param name="key_added" argument="--key-added" type="text" value="louvain" label="Key under which to add the cluster labels (do not change unless you know what you are doing)"/>
        <param name="use_weights" argument="--use-weights" type="boolean" checked="false" label="Use weights from knn graph"/>
        <param name="random_seed" argument="--random-seed" type="integer" value="0" label="Seed for random number generator"/>
      </when>
    </conditional>
  </inputs>

  <outputs>
    <data name="output_h5" format="h5" from_work_dir="output.h5" label="${tool.name} on ${on_string}: Cluster object"/>
    <data name="output_txt" format="tsv" from_work_dir="output.tsv" label="${tool.name} on ${on_string}: Cluster table">
      <filter>output_cluster</filter>
    </data>
  </outputs>

  <tests>
    <test>
      <param name="input_obj_file" value="compute_graph.h5"/>
      <param name="input_format" value="anndata"/>
      <param name="output_format" value="anndata"/>
      <param name="output_txt" value="true"/>
      <param name="default" value="false"/>
      <param name="flavor" value="vtraag"/>
      <param name="resolution" value="1.0"/>
      <param name="random_seed" value="0"/>
      <output name="output_h5" file="find_cluster.h5" ftype="h5" compare="sim_size"/>
      <output name="output_txt" file="find_cluster.tsv" ftype="tsv"/>
    </test>
  </tests>

  <help><![CDATA[
===========================================
Cluster cells into subgroups (`tl.louvain`)
===========================================

Cluster cells using the Louvain algorithm (Blondel et al, 2008) in the implementation
of Traag et al,2017. The Louvain algorithm has been proposed for single-cell
analysis by Levine et al, 2015.

This requires to run `Scanpy ComputeGraph`, first.

It yields `louvain`, generated cluster label.

@HELP@

@VERSION_HISTORY@
]]></help>
  <expand macro="citations">
    <citation type="doi">10.1088/1742-5468/2008/10/P10008</citation>
    <citation type="doi">10.1016/j.cell.2015.05.047</citation>
    <citation type="doi">10.5281/zenodo.35117</citation>
  </expand>
</tool>