Mercurial > repos > iuc > seurat_preprocessing
changeset 1:6bccf5f85f92 draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/seurat_v5 commit 566984b588e88225f0b3f2dae88c6fd084315e7c
| author | iuc |
|---|---|
| date | Tue, 05 Nov 2024 11:54:52 +0000 |
| parents | c3170652bd98 |
| children | |
| files | macros.xml normalize_select_features_scale.xml |
| diffstat | 2 files changed, 10 insertions(+), 4 deletions(-) [+] |
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--- a/macros.xml Wed Sep 11 10:20:38 2024 +0000 +++ b/macros.xml Tue Nov 05 11:54:52 2024 +0000 @@ -2,6 +2,11 @@ <token name="@TOOL_VERSION@">5.0</token> <token name="@VERSION_SUFFIX@">0</token> <token name="@PROFILE@">23.0</token> + <xml name="bio_tools"> + <xrefs> + <xref type="bio.tools">seurat</xref> + </xrefs> + </xml> <xml name="requirements"> <requirements> <requirement type="package" version="@TOOL_VERSION@">r-seurat</requirement> @@ -141,7 +146,7 @@ </data> </xml> <token name="@CMD_inspect_rds_outputs@"><![CDATA[ -write.table(inspect, 'inspect_out.tab', sep="\t", col.names = col.names, row.names = row.names, quote = FALSE) +write.table(inspect, 'inspect_out.tab', sep="\t", col.names = col.names, row.names = row.names, quote = FALSE) ]]> </token> <xml name="plot_out">
--- a/normalize_select_features_scale.xml Wed Sep 11 10:20:38 2024 +0000 +++ b/normalize_select_features_scale.xml Tue Nov 05 11:54:52 2024 +0000 @@ -3,6 +3,7 @@ <macros> <import>macros.xml</import> </macros> + <expand macro="bio_tools"/> <expand macro="requirements"/> <expand macro="version_command"/> <command detect_errors="exit_code"><![CDATA[ @@ -404,7 +405,7 @@ Seurat ====== -Seurat is an R package designed for QC, analysis, and exploration of single-cell RNA-seq data. +Seurat is an R package designed for QC, analysis, and exploration of single-cell RNA-seq data. 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. @@ -444,7 +445,7 @@ Scale and regress the data with ScaleData ========================================= -Scale and center features in the dataset. +Scale and center features in the dataset. If variables are provided in vars.to.regress, they are individually regressed against each feature, and the resulting residuals are then scaled and centered. @@ -454,7 +455,7 @@ SCTransform =========== -Use this function as an alternative to the NormalizeData, FindVariableFeatures, ScaleData workflow. +Use this function as an alternative to the NormalizeData, FindVariableFeatures, ScaleData workflow. Results are saved in a new assay (named SCT by default) with counts being (corrected) counts, data being log1p(counts), scale.data being pearson residuals; sctransform::vst intermediate results are saved in misc slot of new assay.