## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( echo = TRUE, collapse = TRUE, comment = "#>" ) ## ----Installation from Bioconductor, eval = FALSE----------------------------- # if(!require(BiocManager)) install.packages("BiocManager") # BiocManager::install("DEsingle") ## ----Installation from GitHub, eval = FALSE----------------------------------- # if(!require(devtools)) install.packages("devtools") # devtools::install_github("miaozhun/DEsingle", build_vignettes = TRUE) ## ----Load DEsingle, eval = FALSE---------------------------------------------- # library(DEsingle) ## ----Load TestData------------------------------------------------------------ library(DEsingle) data(TestData) ## ----counts------------------------------------------------------------------- dim(counts) counts[1:6, 1:6] ## ----group-------------------------------------------------------------------- length(group) summary(group) ## ----demo1, eval = FALSE------------------------------------------------------ # # Load library and the test data for DEsingle # library(DEsingle) # data(TestData) # # # Specifying the two groups to be compared # # The sample number in group 1 and group 2 is 50 and 100 respectively # group <- factor(c(rep(1,50), rep(2,100))) # # # Detecting the DE genes # results <- DEsingle(counts = counts, group = group) # # # Dividing the DE genes into 3 categories at threshold of FDR < 0.05 # results.classified <- DEtype(results = results, threshold = 0.05) ## ----demo2, eval = FALSE------------------------------------------------------ # # Load library and the test data for DEsingle # library(DEsingle) # library(SingleCellExperiment) # data(TestData) # # # Convert the test data in DEsingle to SingleCellExperiment data representation # sce <- SingleCellExperiment(assays = list(counts = as.matrix(counts))) # # # Specifying the two groups to be compared # # The sample number in group 1 and group 2 is 50 and 100 respectively # group <- factor(c(rep(1,50), rep(2,100))) # # # Detecting the DE genes with SingleCellExperiment input sce # results <- DEsingle(counts = sce, group = group) # # # Dividing the DE genes into 3 categories at threshold of FDR < 0.05 # results.classified <- DEtype(results = results, threshold = 0.05) ## ----extract DE, eval = FALSE------------------------------------------------- # # Extract DE genes at threshold of FDR < 0.05 # results.sig <- results.classified[results.classified$pvalue.adj.FDR < 0.05, ] ## ----extract subtypes, eval = FALSE------------------------------------------- # # Extract three types of DE genes separately # results.DEs <- results.sig[results.sig$Type == "DEs", ] # results.DEa <- results.sig[results.sig$Type == "DEa", ] # results.DEg <- results.sig[results.sig$Type == "DEg", ] ## ----demo3, eval = FALSE------------------------------------------------------ # # Load library # library(DEsingle) # # # Detecting the DE genes in parallelization # results <- DEsingle(counts = counts, group = group, parallel = TRUE) ## ----demo4, eval = FALSE------------------------------------------------------ # # Load library # library(DEsingle) # library(BiocParallel) # # # Set the parameters and register the back-end to be used # param <- MulticoreParam(workers = 18, progressbar = TRUE) # register(param) # # # Detecting the DE genes in parallelization with 18 cores # results <- DEsingle(counts = counts, group = group, parallel = TRUE, BPPARAM = param) ## ----demo5, eval = FALSE------------------------------------------------------ # # Load library # library(DEsingle) # library(BiocParallel) # # # Set the parameters and register the back-end to be used # param <- SnowParam(workers = 8, type = "SOCK", progressbar = TRUE) # register(param) # # # Detecting the DE genes in parallelization with 8 cores # results <- DEsingle(counts = counts, group = group, parallel = TRUE, BPPARAM = param) ## ----help1, eval = FALSE------------------------------------------------------ # # Documentation for DEsingle # ?DEsingle ## ----help2, eval = FALSE------------------------------------------------------ # # Documentation for DEtype # ?DEtype ## ----help3, eval = FALSE------------------------------------------------------ # # Documentation for TestData # ?TestData # ?counts # ?group ## ----sessionInfo-------------------------------------------------------------- sessionInfo()