comparison seurat_read10x.xml @ 2:2d121013176f draft

planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit bbe3c1f7fd8489951f2d90415fe80dd5cf961ca0

1:265dcc5bc1e8

<tool id="seurat_read10x" name="Seurat Read10x" version="@SEURAT_VERSION@_@VERSION@+galaxy0">
<description>Loads 10x data into a serialized seurat R object</description>
  <macros>
      <import>seurat_macros.xml</import>
  </macros>
  <expand macro="requirements" />
<stdio>
<exit_code range="1:" />
</stdio>
<command><![CDATA[
ln -s "$matrix" matrix.mtx;
ln -s "$genes" genes.tsv;
ln -s "$barcodes" barcodes.tsv;

seurat-read-10x.R -d ./

#if $metadata
  --metadata '$metadata'
#end if
#if $min_cells
  --min-cells '$min_cells'

@OUTPUT_OBJECT@

]]></command>
<inputs>
    <param type="data" name="matrix" help="Raw expression quantification as a sparse matrix in Matrix Market format, where each column is a gene and each row is a barcode/cell." format="txt" label="Expression matrix in sparse matrix format (.mtx)" />
    <param type="data" name="genes" help="Matrix market column file for genes" label="Gene table" format="tsv,tabular"/>
    <param type="data" name="barcodes" help="Matrix market row file for genes" label="Barcode/cell table" format="tsv,tabular"/>
    <param label="Cell Metadata" optional="true" name="metadata" argument="--metadata" type="data" format="tsv,tabular" help="File with metdata for the cells, first column should be cell identifiers as used in the cells 10x file."/>
    <param label="Minimum cells to include features" optional="true" name="min_cells" argument="--min-cells" type="integer" help="Include features detected in at least this many cells. Will subset the counts matrix as well. To reintroduce excluded features, create a new object with a lower cutoff."/>
    <param label="Minimum features to include cells" optional="true" name="min_features" argument="--min-features" type="integer" help="Include cells where at least this many features are detected."/>
    <expand macro="output_object_params"/>
</inputs>

  **What it does**

  @SEURAT_INTRO@

  **Read 10x-Genomics-formatted mtx directory (`read_10x_mtx`)**

  The mtx directory should contain:

  1) Raw expression quantification as a sparse matrix in Matrix Market format, where the each column is a gene and each row is a barcode/cell.

  2) A gene table of at least two columns where the first column gives the gene IDs.

  The above-mentioned files can be obtained by running `EBI SCXA Data Retrieval`
  with a dataset accession. Otherwise, they need to be provided as separate Galaxy
  datasets.

  **Inputs**
      * Raw expression quantification as a sparse matrix in Matrix Market format, where the each column is a gene and each row is a barcode/cell.
      * A gene table of at least two columns where the first column gives the gene IDs.
      * A barcode/cell table of at least one column giving the barcode/cell IDs.
      * Optionally, a file with cell metadata.

  **Outputs**
      * R object for Seurat

2:2d121013176f

<tool id="seurat_read10x" name="Seurat Read10x" version="@SEURAT_VERSION@+galaxy1">
<description>Loads Tabular or 10x data into a serialized seurat R object</description>
  <macros>
      <import>seurat_macros.xml</import>
  </macros>
  <expand macro="requirements" />
<stdio>
<exit_code range="1:" />
</stdio>
<command><![CDATA[

#if str($input.format) == "mtx":
    ln -s "$matrix" matrix.mtx;
    ln -s "$genes" genes.tsv;
    ln -s "$barcodes" barcodes.tsv;
# end if

seurat-read-10x.R
#if str($input.format) == "mtx":
 -d ./
#else
 -f $input.file
# end if
#if $metadata
  --metadata '$metadata'
#end if
#if $min_cells
  --min-cells '$min_cells'

@OUTPUT_OBJECT@

]]></command>
<inputs>
     <conditional name="input" label="Input expression data">
       <param type="select" name="format" label="Choose the format of the input" help="10X MTX or tabular">
         <option value="mtx" selected="true">10X-type MTX</option>
         <option value="tab" selected="true">tab-delimited text</option>
       </param>
       <when value="tab">
         <param type="data" name="file" label="Expression table" help="Tab-delimted expression table" format="tabular"/>
       </when>
       <when value="mtx">
        <param type="data" name="matrix" help="Raw expression quantification as a sparse matrix in Matrix Market format, where each column is a gene and each row is a barcode/cell." format="txt" label="Expression matrix in sparse matrix format (.mtx)" />
        <param type="data" name="genes" help="Matrix market column file for genes" label="Gene table" format="tsv,tabular"/>
        <param type="data" name="barcodes" help="Matrix market row file for genes" label="Barcode/cell table" format="tsv,tabular"/>
       </when>
     </conditional>
    <param label="Cell Metadata" optional="true" name="metadata" argument="--metadata" type="data" format="tsv,tabular" help="File with metdata for the cells, first column should be cell identifiers as used in the cells 10x file."/>
    <param label="Minimum cells to include features" optional="true" name="min_cells" argument="--min-cells" type="integer" help="Include features detected in at least this many cells. Will subset the counts matrix as well. To reintroduce excluded features, create a new object with a lower cutoff."/>
    <param label="Minimum features to include cells" optional="true" name="min_features" argument="--min-features" type="integer" help="Include cells where at least this many features are detected."/>
    <expand macro="output_object_params"/>
</inputs>

  **What it does**

  @SEURAT_INTRO@

  **Read expression data from a tabular file or a 10x-Genomics-formatted mtx directory (`read_10x_mtx`)**

  For mtx, the  directory should contain:

  1) Raw expression quantification as a sparse matrix in Matrix Market format, where the each column is a gene and each row is a barcode/cell.

  2) A gene table of at least two columns where the first column gives the gene IDs.

  The above-mentioned files can be obtained by running `EBI SCXA Data Retrieval`
  with a dataset accession. Otherwise, they need to be provided as separate Galaxy
  datasets.

  **Inputs**
      * A tabular file of expression data OR
          * Raw expression quantification as a sparse matrix in Matrix Market format, where the each column is a gene and each row is a barcode/cell.
          * A gene table of at least two columns where the first column gives the gene IDs.
          * A barcode/cell table of at least one column giving the barcode/cell IDs.
      * Optionally, a file with cell metadata.

  **Outputs**
      * R object for Seurat