comparison scanpy-find-variable-genes.xml @ 21:79da59a0b180 draft

"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 69b3fd29988bdcbf30d38572b75793ab74110acd-dirty"

20:24fca62faafd

<?xml version="1.0" encoding="utf-8"?>
<tool id="scanpy_find_variable_genes" name="Scanpy FindVariableGenes" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
  <description>based on normalised dispersion of expression</description>
  <macros>
    <import>scanpy_macros2.xml</import>
  </macros>
  <expand macro="requirements"/>

#if $span
    --span ${span}
#end if
    --n-bins '${n_bin}'
    ${filter}
    @INPUT_OPTS@
    @OUTPUT_OPTS@
]]></command>

  <inputs>

    <param name="span" argument="--span" type="float" min="0" max="1" value="0.3" optional="true" 
           label="The fraction of the data (cells) used when estimating the variance in the loess model fit if flavor='seurat_v3'"/>
    <param name="n_bin" argument="--n-bins" type="integer" value="20" label="Number of bins for binning the mean expression"/>
    <param name="filter" argument="--subset" type="boolean" truevalue="--subset" falsevalue="" checked="false"
           label="Remove genes not marked as highly variable" help="When set, inplace subset to highly-variable genes, otherwise only flag highly-variable genes."/>
    <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."/>
  </inputs>

  <outputs>
    <expand macro="output_data_obj" description="Variable genes"/>
  </outputs>

21:79da59a0b180

<?xml version="1.0" encoding="utf-8"?>
<tool id="scanpy_find_variable_genes" name="Scanpy FindVariableGenes" version="@TOOL_VERSION@+galaxy1" profile="@PROFILE@">
  <description>based on normalised dispersion of expression</description>
  <macros>
    <import>scanpy_macros2.xml</import>
  </macros>
  <expand macro="requirements"/>

#if $span
    --span ${span}
#end if
    --n-bins '${n_bin}'
    ${filter}
#if $batch_key
    --batch-key ${batch_key}
#end if
    @INPUT_OPTS@
    @OUTPUT_OPTS@
]]></command>

  <inputs>

    <param name="span" argument="--span" type="float" min="0" max="1" value="0.3" optional="true" 
           label="The fraction of the data (cells) used when estimating the variance in the loess model fit if flavor='seurat_v3'"/>
    <param name="n_bin" argument="--n-bins" type="integer" value="20" label="Number of bins for binning the mean expression"/>
    <param name="filter" argument="--subset" type="boolean" truevalue="--subset" falsevalue="" checked="false"
           label="Remove genes not marked as highly variable" help="When set, inplace subset to highly-variable genes, otherwise only flag highly-variable genes."/>
    <param name="batch_key" argument="--batch-key" type="text" label="Batch key" optional="true" 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."/>
  </inputs>

  <outputs>
    <expand macro="output_data_obj" description="Variable genes"/>
  </outputs>