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Commit message:
planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 0463f230d18201c740851d72e31a5024f391207f |
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modified:
seurat_macros.xml seurat_read10x.xml |
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| diff -r 1b8566f3c1d0 -r 265dcc5bc1e8 seurat_macros.xml --- a/seurat_macros.xml Wed Apr 03 11:18:21 2019 -0400 +++ b/seurat_macros.xml Mon Nov 25 06:10:49 2019 -0500 |
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| @@ -1,34 +1,110 @@ <?xml version="1.0"?> <macros> - - <token name="@VERSION@">0.0.5</token> - + <token name="@VERSION@">0.0.6</token> + <token name="@SEURAT_VERSION@">3.1.1</token> <xml name="requirements"> <requirements> <requirement type="package" version="@VERSION@">seurat-scripts</requirement> </requirements> </xml> - <xml name="version"> <version_command><![CDATA[ echo $(R --version | grep version | grep -v GNU)", seurat version" $(R --vanilla --slave -e "library(seurat); cat(sessionInfo()\$otherPkgs\$seurat\$Version)" 2> /dev/null | grep -v -i "WARNING: ") ]]></version_command> </xml> + <xml name="input_object_params"> + <conditional name="input" label="Input format"> + <param type="select" name="format" label="Choose the format of the input" help="RData, Loom or AnnData"> + <option value="rds_seurat" selected="true">RDS with a Seurat object</option> + <option value="loom">Loom</option> + <option value="anndata">AnnData</option> + <option value="rds_sce">RDS with a Single Cell Experiment object</option> + </param> + <when value="anndata"> + <param type="data" name="anndata_file" label="AnnData file" help="The AnnData format provided by Scanpy" format="h5,h5ad"/> + </when> + <when value="loom"> + <param type="data" name="loom_file" label="Loom file" help="Input as Loom v? file" format="h5,h5loom"/> + </when> + <when value="rds_seurat"> + <param type="data" name="rds_seurat_file" label="RDS file" help="Input as RDS file with Seurat 3 object" format="rdata"/> + </when> + <when value="rds_sce"> + <param type="data" name="rds_sce_file" label="RDS file" help="Input as RDS file with Single Cell Experiment object" format="rdata"/> + </when> + </conditional> + </xml> + + <token name="@INPUT_OBJECT@"> + #if $input.format == "anndata" + --input-object-file '$input.anndata_file' --input-format anndata + #else if $input.format == "loom" + --input-object-file '$input.loom_file' --input-format loom + #else if $input.format == "rds_seurat" + --input-object-file '$input.rds_seurat_file' --input-format seurat + #else if $input.format == "rds_sce" + --input-object-file '$input.rds_sce_file' --input-format singlecellexperiment + #end if + </token> + + <xml name="output_object_params"> + <param type="select" name="format" label="Choose the format of the output" help="Seurat, Single Cell Experiment or Loom"> + <option value="rds_seurat" selected="true">RDS with a Seurat object</option> + <option value="loom">Loom</option> + <option value="rds_sce">RDS with a Single Cell Experiment object</option> + </param> + </xml> + + <xml name="output_files"> + <data name="loom_file" from_work_dir="seurat_obj.loom" format="h5" label="${tool.name} on ${on_string}: Seurat Loom"> + <filter>format == 'loom'</filter> + </data> + <data name="rds_seurat_file" format="rdata" label="${tool.name} on ${on_string}: Seurat RDS"> + <filter>format == 'rds_seurat'</filter> + </data> + <data name="rds_sce_file" format="rdata" label="${tool.name} on ${on_string}: Seurat Single Cell Experiment RDS"> + <filter>format == 'rds_sce'</filter> + </data> + </xml> + + <token name="@OUTPUT_OBJECT@"> + #if $format == "anndata" + --output-object-file '$anndata_file' --output-format anndata + #else if $format == "loom" + --output-object-file seurat_obj.loom --output-format loom + #else if $format == "rds_seurat" + --output-object-file '$rds_seurat_file' --output-format seurat + #else if $format == "rds_sce" + --output-object-file '$rds_sce_file' --output-format singlecellexperiment + #end if + </token> + <xml name="genes-use-input"> - <param name="genes_use" argument="--genes-use" optional="true" type="data" format="tsv, txt" label="Genes to use" help="A file with gene names to use in construction of SNN graph if building directly based on expression data rather than a dimensionally reduced representation (i.e. PCs)."/> + <param name="genes_use" argument="--genes-use" optional="true" type="data" format="tsv,txt,tabular" label="Genes to use" help="A file with gene names to use in construction of SNN graph if building directly based on expression data rather than a dimensionally reduced representation (i.e. PCs)."/> </xml> <xml name="dims-use-input"> <param name="dims_use" argument="--dims-use" min="1" optional="true" type="integer" label="PCA Dimensions to use" help="Number of PCs (dimensions) to use in construction of the SNN graph."/> </xml> + <token name="@SEURAT_INTRO@"><![CDATA[ +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. + ]]></token> + <token name="@VERSION_HISTORY@"><![CDATA[ **Version history** -0.0.1: Initial contribution. Maria Doyle, https://github.com/mblue9. +3.1.1_0.0.6+galaxy0: Moved to Seurat 3. + + Find clusters: removed dims-use, k-param, prune-snn. 2.3.1+galaxy0: Improved documentation and further exposition of all script's options. Pablo Moreno, Jonathan Manning and Ni Huang, Expression Atlas team https://www.ebi.ac.uk/gxa/home at EMBL-EBI https://www.ebi.ac.uk/. Parts obtained from wrappers from Christophe Antoniewski(https://github.com/drosofff) and Lea Bellenger(https://github.com/bellenger-l). + +0.0.1: Initial contribution. Maria Doyle, https://github.com/mblue9. ]]></token> |
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| diff -r 1b8566f3c1d0 -r 265dcc5bc1e8 seurat_read10x.xml --- a/seurat_read10x.xml Wed Apr 03 11:18:21 2019 -0400 +++ b/seurat_read10x.xml Mon Nov 25 06:10:49 2019 -0500 |
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| @@ -1,4 +1,4 @@ -<tool id="seurat_read10x" name="Seurat Read10x" version="2.3.1+galaxy1"> +<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> @@ -12,15 +12,32 @@ ln -s "$genes" genes.tsv; ln -s "$barcodes" barcodes.tsv; -seurat-read-10x.R -d ./ -o "$R_seurat_serialized" +seurat-read-10x.R -d ./ + +#if $metadata + --metadata '$metadata' +#end if +#if $min_cells + --min-cells '$min_cells' +#end if +#if $min_features + --min-features '$min_features' +#end if + +@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> <outputs> - <data name="R_seurat_serialized" format="rdata" label="${tool.name} on ${on_string}: RData file" /> + <expand macro="output_files"/> </outputs> <tests> @@ -28,7 +45,7 @@ <param name="matrix" ftype="txt" value="test_matrix.txt"/> <param name="genes" ftype="txt" value="test_genes.txt"/> <param name="barcodes" ftype="txt" value="test_barcodes.txt"/> - <output name="R_seurat_serialized" ftype="rdata" value="out_scale.rds" compare="sim_size"/> + <output name="rds_seurat_file" ftype="rdata" value="out_scale.rds" compare="sim_size"/> </test> </tests> @@ -38,10 +55,7 @@ **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. See the `Seurat Guided Clustering tutorial`_ for more information. + @SEURAT_INTRO@ **Read 10x-Genomics-formatted mtx directory (`read_10x_mtx`)** @@ -61,6 +75,7 @@ * 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 |