view scanpy-plot-embedding.xml @ 0:c63bc0b71865 draft

"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 4846776f55931e176f7e77af7c185ec6fec7d142"

<?xml version="1.0" encoding="utf-8"?>
<tool id="scanpy_plot_embed" name="Scanpy PlotEmbed" version="@TOOL_VERSION@+galaxy0">
  <description>visualise cell embeddings</description>
  <macros>
    <import>scanpy_macros2.xml</import>
  </macros>
  <expand macro="requirements"/>
  <command detect_errors="exit_code"><![CDATA[
ln -s '${input_obj_file}' input.h5 &&
PYTHONIOENCODING=utf-8 scanpy-cli plot embed
    @INPUT_OPTS@
    --basis '${basis}'
    --color '${color_by}'
    ${use_raw}
    --legend-loc '${legend_loc}'
    --legend-fontsize '${legend_fontsize}'
#if $point_size
    --size ${point_size}
#end if
    @PLOT_OPTS@
]]></command>

  <inputs>
    <expand macro="input_object_params"/>
    <param name="basis" argument="--basis" type="text" label="Name of the embedding to plot"/>
    <param name="color_by" argument="--color" type="text" label="Color by attributes, comma separated texts"/>
    <param name="use_raw" argument="--use-raw" type="boolean" checked="true" truevalue="--use-raw" falsevalue="--no-raw" label="Use raw attributes if present"/>
    <param name="legend_loc" argument="--legend-loc" type="select" label="Location of legend">
      <option value="right margin" selected="true">Right margin</option>
      <option value="on data">On data</option>
    </param>
    <param name="legend_fontsize" argument="--legend-fontsize" type="integer" value="15" label="Legend font size"/>
    <param name="point_size" argument="--size" type="integer" optional="true" label="Point size"
           help="Automatically determined if not specified."/>
    <expand macro="output_plot_params"/>
  </inputs>

  <outputs>
    <data name="output_png" format="png" from_work_dir="output.png" label="${tool.name} on ${on_string}: embedding plot"/>
  </outputs>

  <tests>
    <test>
      <param name="input_obj_file" value="find_cluster.h5"/>
      <param name="input_format" value="anndata"/>
      <param name="color_by" value="louvain"/>
      <output name="output_png" file="run_tsne.png" ftype="png" compare="sim_size"/>
    </test>
  </tests>

  <help><![CDATA[
=============================================================
Plot embeddings of a given method of dimensionality reduction
=============================================================

It yields a scatter plot in png format, wherein cells are placed in space of
reduced dimensionality and coloured by attribute of choice.

Requires calculating the specified embeddings first. For example, to make
UMAP/TSNE plots, run `Scanpy RunUMAP`/`Scanpy RunTSNE` first, then enter
"umap"/"tsne" as the name of the embedding to plot here.

@HELP@

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