Previous changeset 1:7319f83ae734 (2019-12-09) Next changeset 3:7a5cd7987b03 (2020-01-18) |
Commit message:
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/seurat commit 3cf715ec11e2c9944f46572e324e5b2db5aa151f" |
modified:
Seurat.R seurat.xml test-data/out.html |
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diff -r 7319f83ae734 -r 321bdd834266 Seurat.R --- a/Seurat.R Mon Dec 09 14:32:16 2019 -0500 +++ b/Seurat.R Thu Dec 19 02:42:56 2019 -0500 |
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@@ -23,7 +23,7 @@ #' --- #+ echo=F, warning = F, message=F -options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) +options(show.error.messages = F, error = function(){cat(geterrmessage(), file = stderr()); q("no", 1, F)}) showcode <- as.logical(params$showcode) warn <- as.logical(params$warn) varstate <- as.logical(params$varstate) @@ -33,7 +33,7 @@ tsne <- as.logical(params$tsne) heatmaps <- as.logical(params$heatmaps) -# we need that to not crash galaxy with an UTF8 error on German LC settings. +# we need that to not crash Galaxy with an UTF-8 error on German LC settings. loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8") @@ -57,52 +57,52 @@ print(paste0("Logfold change threshold", logfc_threshold)) #+ echo = FALSE -if(showcode == TRUE){print("Read in data, generate inital Seurat object")} +if(showcode == TRUE) print("Read in data, generate inital Seurat object") #+ echo = `showcode`, warning = `warn`, message = F -counts <- read.delim(params$counts, row.names=1) +counts <- read.delim(params$counts, row.names = 1) seuset <- Seurat::CreateSeuratObject(counts = counts, min.cells = min_cells, min.features = min_genes) #+ echo = FALSE -if(showcode == TRUE && vlnfeat == TRUE){print("Raw data vizualization")} +if(showcode == TRUE && vlnfeat == TRUE) print("Raw data vizualization") #+ echo = `showcode`, warning = `warn`, include=`vlnfeat` -Seurat::VlnPlot(object = seuset, features = c("nFeature_RNA", "nCount_RNA"), axis="v") +Seurat::VlnPlot(object = seuset, features = c("nFeature_RNA", "nCount_RNA")) Seurat::FeatureScatter(object = seuset, feature1 = "nCount_RNA", feature2 = "nFeature_RNA") #+ echo = FALSE -if(showcode == TRUE){print("Filter and normalize for UMI counts")} +if(showcode == TRUE) print("Filter and normalize for UMI counts") #+ echo = `showcode`, warning = `warn` seuset <- subset(seuset, subset = `nCount_RNA` > low_thresholds & `nCount_RNA` < high_thresholds) -seuset <- Seurat::NormalizeData(seuset, normalizeation.method = "LogNormalize", scale.factor = 10000) +seuset <- Seurat::NormalizeData(seuset, normalization.method = "LogNormalize", scale.factor = 10000) #+ echo = FALSE -if(showcode == TRUE && featplot == TRUE){print("Variable Genes")} +if(showcode == TRUE && featplot == TRUE) print("Variable Genes") #+ echo = `showcode`, warning = `warn`, include = `featplot` seuset <- Seurat::FindVariableFeatures(object = seuset, selection.method = "mvp") Seurat::VariableFeaturePlot(seuset, cols = c("black", "red"), selection.method = "disp") seuset <- Seurat::ScaleData(object = seuset, vars.to.regress = "nCount_RNA") #+ echo = FALSE -if(showcode == TRUE && PCplots == TRUE){print("PCA Visualization")} +if(showcode == TRUE && PCplots == TRUE) print("PCA Visualization") #+ echo = `showcode`, warning = `warn`, include = `PCplots` -seuset <- Seurat::RunPCA(seuset, npcs=numPCs) +seuset <- Seurat::RunPCA(seuset, npcs = numPCs) Seurat::VizDimLoadings(seuset, dims = 1:2) -Seurat::DimPlot(seuset, dims = c(1,2), reduction="pca") -Seurat::DimHeatmap(seuset, dims=1:numPCs, nfeatures=30, reduction="pca") +Seurat::DimPlot(seuset, dims = c(1,2), reduction = "pca") +Seurat::DimHeatmap(seuset, dims = 1:numPCs, nfeatures = 30, reduction = "pca") seuset <- Seurat::JackStraw(seuset, dims=numPCs, reduction = "pca", num.replicate = 100) seuset <- Seurat::ScoreJackStraw(seuset, dims = 1:numPCs) Seurat::JackStrawPlot(seuset, dims = 1:numPCs) Seurat::ElbowPlot(seuset, ndims = numPCs, reduction = "pca") #+ echo = FALSE -if(showcode == TRUE && tsne == TRUE){print("tSNE")} +if(showcode == TRUE && tsne == TRUE) print("tSNE") #+ echo = `showcode`, warning = `warn`, include = `tsne` seuset <- Seurat::FindNeighbors(object = seuset) seuset <- Seurat::FindClusters(object = seuset) seuset <- Seurat::RunTSNE(seuset, dims = 1:numPCs, resolution = resolution) -Seurat::DimPlot(seuset, reduction="tsne") +Seurat::DimPlot(seuset, reduction = "tsne") #+ echo = FALSE -if(showcode == TRUE && heatmaps == TRUE){print("Marker Genes")} +if(showcode == TRUE && heatmaps == TRUE) print("Marker Genes") #+ 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) |
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diff -r 7319f83ae734 -r 321bdd834266 seurat.xml --- a/seurat.xml Mon Dec 09 14:32:16 2019 -0500 +++ b/seurat.xml Thu Dec 19 02:42:56 2019 -0500 |
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@@ -1,8 +1,13 @@ -<tool id="seurat" name="Seurat" version="2.3.4"> +<tool id="seurat" name="Seurat" version="@TOOL_VERSION@"> <description>- toolkit for exploration of single-cell RNA-seq data</description> + <macros> + <token name="@TOOL_VERSION@">3.1.2</token> + </macros> <requirements> - <requirement type="package" version="3.1.0">r-seurat</requirement> - <requirement type="package" version="1.16">r-rmarkdown</requirement> + <requirement type="package" version="@TOOL_VERSION@">r-seurat</requirement> + <requirement type="package" version="2.0">r-rmarkdown</requirement> + <!-- Need to pin pandoc due to https://github.com/rstudio/rmarkdown/issues/1740 --> + <requirement type="package" version="2.7.3">pandoc</requirement> </requirements> <command detect_errors="exit_code"><![CDATA[ #if "vln" in $meta.plots: |
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diff -r 7319f83ae734 -r 321bdd834266 test-data/out.html --- a/test-data/out.html Mon Dec 09 14:32:16 2019 -0500 +++ b/test-data/out.html Thu Dec 19 02:42:56 2019 -0500 |
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@@ -1,18 +1,17 @@ <!DOCTYPE html> -<html xmlns="http://www.w3.org/1999/xhtml"> +<html> <head> <meta charset="utf-8" /> -<meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <meta name="generator" content="pandoc" /> <meta http-equiv="X-UA-Compatible" content="IE=EDGE" /> <meta name="author" content="Performed using Galaxy" /> -<meta name="date" content="2019-12-08" /> +<meta name="date" content="2019-12-16" /> <title>Seurat Analysis</title> @@ -332,6 +331,7 @@ border: none; display: inline-block; border-radius: 4px; + background-color: transparent; } .tabset-dropdown > .nav-tabs.nav-tabs-open > li { @@ -365,17 +365,17 @@ <h1 class="title toc-ignore">Seurat Analysis</h1> <h4 class="author">Performed using Galaxy</h4> -<h4 class="date">2019-12-08</h4> +<h4 class="date">2019-12-16</h4> </div> <pre><code>## [1] "Read in data, generate inital Seurat object"</code></pre> -<pre class="r"><code>counts <- read.delim(params$counts, row.names=1) +<pre class="r"><code>counts <- read.delim(params$counts, row.names = 1) seuset <- Seurat::CreateSeuratObject(counts = counts, min.cells = min_cells, min.features = min_genes)</code></pre> <pre><code>## [1] "Filter and normalize for UMI counts"</code></pre> <pre class="r"><code>seuset <- subset(seuset, subset = `nCount_RNA` > low_thresholds & `nCount_RNA` < high_thresholds) -seuset <- Seurat::NormalizeData(seuset, normalizeation.method = "LogNormalize", scale.factor = 10000)</code></pre> +seuset <- Seurat::NormalizeData(seuset, normalization.method = "LogNormalize", scale.factor = 10000)</code></pre> <pre><code>## [1] "Variable Genes"</code></pre> <pre class="r"><code>seuset <- Seurat::FindVariableFeatures(object = seuset, selection.method = "mvp") Seurat::VariableFeaturePlot(seuset, cols = c("black", "red"), selection.method = "disp")</code></pre> |