<tool id="seurat_find_markers" name="Seurat FindMarkers" version="2.3.1+galaxy1">
    <description>find markers (differentially expressed genes)</description>
    <macros>
        <import>seurat_macros.xml</import>
    </macros>
    <expand macro="requirements" />
    <expand macro="version" />
    <command detect_errors="exit_code"><![CDATA[
seurat-find-markers.R

--input-object-file '$input'
--output-text-file output.txt

#if $genes_use:
  --genes-use '$genes_use'
#end if

#if str($logfc_threshold):
  --logfc-threshold '$logfc_threshold'
#end if

#if str($adv.min_pct):
  --min-pct '$adv.min_pct'
#end if

#if str($adv.min_diff_pct):
  --min-diff-pct '$adv.min_diff_pct'
#end if

#if $adv.only_pos:
  --only-pos '$adv.only_pos'
#end if

--test-use '$adv.test_use'

#if str($max_cells_per_ident):
  --max-cells-per-ident '$max_cells_per_ident'
#end if

#if str($min_cells_per_gene):
  --min-cells-gene '$min_cells_per_gene'
#end if

#if str($min_cells_group):
  --min-cells-group '$min_cells_group'
#end if


]]></command>

    <inputs>
        <param name="input" type="data" format="rdata" label="RDS object" />
        <expand macro="genes-use-input"/>
        <param name="logfc_threshold" label="LogFC logfc_threshold" optional="true" argument="--logfc-threshold" type="float" help="Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is 0.25 Increasing logfc.threshold speeds up the function, but can miss weaker signals."/>
        <param name="max_cells_per_ident" label="Max cells per ident" optional="true" argument="--max-cells-per-ident" type="integer" help="Down sample each identity class to a max number. Default is no downsampling. Not activated by default (set to Inf)."/>
        <param name="min_cells_per_gene" label="Min cells per gene" optional="true" argument="--min-cells-gene" type="integer" help="Minimum number of cells expressing the gene in at least one of the two groups, currently only used for poisson and negative binomial tests."/>
        <param name="min_cells_group" label="Min cells in one of the groups" optional="true" argument="--min-cells-group" type="integer"/>
        <section name="adv" title="Advanced Options">
            <param name="min_pct" type="float" label="Min Pct" optional="true" help="Only test genes that are detected in a minimum fraction of min.pct cells in either of the two populations. Meant to speed up the function by not testing genes that are very infrequently expressed. Default is 0.1."/>
            <param name="min_diff_pct" type="float" label="Min diff Pct" optional="true" help="Only test genes that show a minimum difference in the fraction of detection between the two groups. Set to -Inf by default."/>
            <param name="only_pos" type="boolean" label="Only positive markers" truevalue="TRUE" falsevalue="" help="Only return positive markers (FALSE by default)."/>
            <param name="test_use" type="select" label="Test to use" help="">
              <option value="wilcox" selected="true">Wilcoxon</option>
              <option value="bimod">Bi-modal</option>
              <option value="roc">ROC</option>
              <option value="t">t-Test</option>
              <option value="tobit">tobit</option>
              <option value="poisson">Poisson</option>
              <option value="negbinom">Negative binomia</option>
              <option value="MAST">MAST</option>
              <option value="DESeq2">DESeq2</option>
            </param>
        </section>
    </inputs>

    <outputs>
        <data name="output" format="txt" from_work_dir="output.txt" label="${tool.name} on ${on_string}: Text file"/>
    </outputs>

    <tests>
        <test>
            <param name="input" ftype="rdata" value="out_runtsne.rds"/>
            <output name="output" ftype="txt" value="out_findmark.txt"/>
        </test>
    </tests>
    <help><![CDATA[
.. class:: infomark

**What it does**

Seurat_ is a toolkit for quality control, analysis, and exploration of single cell RNA sequencing data.
It is developed and maintained by the `Satija Lab`_ at NYGC. Seurat aims to enable users to identify and
interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse
types of single cell data.

This tool finds markers (differentially expressed genes) for each of the identity classes in a dataset. It outputs a text file containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.)

-----

**Inputs**

    * RDS object

-----

**Outputs**

    * Text file

.. _Seurat: https://www.nature.com/articles/nbt.4096
.. _Satija Lab: https://satijalab.org/seurat/

@VERSION_HISTORY@
]]></help>
      <expand macro="citations" />
</tool>