# HG changeset patch # User iuc # Date 1634831840 0 # Node ID c4db6ec33fecc27f098d0b145aa138f9473713cd # Parent 828324f3292fb1d8630726cd651c5cc44be911ef "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/seurat commit 7681c9101062f58ac4eb296a98b1644d4ed2340a" diff -r 828324f3292f -r c4db6ec33fec Seurat.R --- a/Seurat.R Thu Jun 10 17:19:49 2021 +0000 +++ b/Seurat.R Thu Oct 21 15:57:20 2021 +0000 @@ -115,6 +115,6 @@ #+ echo = `showcode`, warning = `warn`, include = `heatmaps` markers <- Seurat::FindAllMarkers(seuset, only.pos = TRUE, min.pct = min_pct, logfc.threshold = logfc_threshold) top10 <- dplyr::group_by(markers, cluster) -top10 <- dplyr::top_n(top10, 10, avg_logFC) +top10 <- dplyr::top_n(top10, 10, avg_log2FC) Seurat::DoHeatmap(seuset, features = top10$gene) # nolint end diff -r 828324f3292f -r c4db6ec33fec seurat.xml --- a/seurat.xml Thu Jun 10 17:19:49 2021 +0000 +++ b/seurat.xml Thu Oct 21 15:57:20 2021 +0000 @@ -1,11 +1,11 @@ - toolkit for exploration of single-cell RNA-seq data - 3.2.2 + 4.0.5 r-seurat - r-rmarkdown + r-rmarkdown
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## [1] "Read in data, generate inital Seurat object"
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counts <- read.delim(params$counts, row.names = 1)
-seuset <- Seurat::CreateSeuratObject(counts = counts, min.cells = min_cells, min.features = min_genes)
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## [1] "Filter and normalize for UMI counts"
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seuset <- subset(seuset, subset = `nCount_RNA` > low_thresholds & `nCount_RNA` < high_thresholds)
-seuset <- Seurat::NormalizeData(seuset, normalization.method = "LogNormalize", scale.factor = 10000)
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## [1] "Variable Genes"
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seuset <- Seurat::FindVariableFeatures(object = seuset, selection.method = "mvp")
-Seurat::VariableFeaturePlot(seuset, cols = c("black", "red"), selection.method = "disp")
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seuset <- Seurat::ScaleData(object = seuset, vars.to.regress = "nCount_RNA")
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## Regressing out nCount_RNA
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## Centering and scaling data matrix
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