Showing content from https://www.bioconductor.org/packages/release/bioc/html/../vignettes/SiPSiC/inst/doc/SiPSiC.R below:
## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) suppressPackageStartupMessages({library(SiPSiC)}) ## ----setup, eval=FALSE-------------------------------------------------------- # if (!require("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("SiPSiC") ## ----Example, warning=FALSE--------------------------------------------------- library(SiPSiC) geneCountsMatrix <- matrix(rpois(16, lambda = 10), ncol = 4, nrow = 4) geneCountsMatrix <- as(geneCountsMatrix, "dgCMatrix") ## Make sure your matrix is indeed a sparse matrix (of type dgCMatrix)! rownames(geneCountsMatrix) <- c("Gene1", "Gene2", "Gene3", "Gene4") colnames(geneCountsMatrix) <- c("Cell1", "Cell2", "Cell3", "Cell4") assayData <- SingleCellExperiment(assays = list(counts = geneCountsMatrix)) pathwayGenesList <- c("Gene1", "Gene2", "Gene4") scoresAndIndices <- getPathwayScores(counts(assayData), pathwayGenesList) # The third parameter, percentForNormalization, is optional; If not specified, its value is set to 5. pathwayScoresOfCells <- scoresAndIndices$pathwayScores pathwayGeneIndices <- scoresAndIndices$index ## ----------------------------------------------------------------------------- sessionInfo()
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