view scanpy-normalise-data.xml @ 0:1dda36e73482 draft

planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 9bf9a6e46a330890be932f60d1d996dd166426c4

<?xml version="1.0" encoding="utf-8"?>
<tool id="scanpy_normalise_data" name="Scanpy NormaliseData" version="@TOOL_VERSION@+galaxy1">
  <description>to make all cells having the same total expression</description>
  <macros>
    <import>scanpy_macros.xml</import>
  </macros>
  <expand macro="requirements"/>
  <command detect_errors="exit_code"><![CDATA[
ln -s '${input_obj_file}' input.h5 &&
PYTHONIOENCODING=utf-8 scanpy-normalise-data.py
    -i input.h5
    -f '${input_format}'
    -o output.h5
    -F '${output_format}'
    -s '${scale_factor}'
    #if $save_raw
        '${save_raw}'
    #end if
    @EXPORT_MTX_OPTS@
]]></command>

  <inputs>
    <expand macro="input_object_params"/>
    <expand macro="output_object_params"/>
    <param name="scale_factor" argument="--scale-factor" type="float" value="1e4" label="Target number to normalise to" help="Aimed counts per cell after normalisation, default: 1e4"/>
    <param name="save_raw" argument="--save-raw" type="boolean" truevalue="--save-raw" falsevalue="" checked="true" label="Save pre-normalised data" help="Save raw quantification in log scale before normalisation."/>
    <expand macro="export_mtx_params"/>
  </inputs>

  <outputs>
    <data name="output_h5" format="h5" from_work_dir="output.h5" label="${tool.name} on ${on_string}: Normalized data" />
    <expand macro="export_mtx_outputs"/>
  </outputs>

  <tests>
    <test>
      <param name="input_obj_file" value="filter_genes.h5"/>
      <param name="input_format" value="anndata"/>
      <param name="output_format" value="anndata"/>
      <param name="scale_factor" value="1e4"/>
      <param name="save_raw" value="false"/>
      <output name="output_h5" file="normalise_data.h5" ftype="h5" compare="sim_size"/>
    </test>
  </tests>

  <help><![CDATA[
=========================================================
Normalize total counts per cell (`pp.normalize_per_cell`)
=========================================================

Normalize each cell by total counts over all genes, so that every cell has
the same total count after normalization.

Similar functions are used, for example, by Seurat, Cell Ranger or SPRING.

@HELP@

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