Mercurial > repos > ebi-gxa > seurat_read10x
diff seurat_read10x.xml @ 0:1b8566f3c1d0 draft
planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit 9bf9a6e46a330890be932f60d1d996dd166426c4
author | ebi-gxa |
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date | Wed, 03 Apr 2019 11:18:21 -0400 |
parents | |
children | 265dcc5bc1e8 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/seurat_read10x.xml Wed Apr 03 11:18:21 2019 -0400 @@ -0,0 +1,75 @@ +<tool id="seurat_read10x" name="Seurat Read10x" version="2.3.1+galaxy1"> +<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 "$barcodes" barcodes.tsv; + +seurat-read-10x.R -d ./ -o "$R_seurat_serialized" +]]></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"/> +</inputs> +<outputs> + <data name="R_seurat_serialized" format="rdata" label="${tool.name} on ${on_string}: RData file" /> +</outputs> + +<tests> + <test> + <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"/> + </test> +</tests> + + +<help><![CDATA[ + .. class:: infomark + + **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. + + **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. + + 3) A barcode/cell table of at least one column giving the barcode/cell 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. + + **Outputs** + * R object for Seurat + + .. _Seurat: https://www.nature.com/articles/nbt.4096 + .. _Satija Lab: https://satijalab.org/seurat/ + .. _Seurat Guided Clustering tutorial: https://satijalab.org/seurat/pbmc3k_tutorial.html + +@VERSION_HISTORY@ +]]></help> +<expand macro="citations"/> +</tool>