## ----options, include=FALSE, echo=FALSE--------------------------------------- library(BiocStyle) knitr::opts_chunk$set(warning=FALSE, error=FALSE, message=FALSE) ## ----eval=FALSE--------------------------------------------------------------- # if (!require("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # BiocManager::install("scDDboost") ## ----echo=FALSE--------------------------------------------------------------- library(ggplot2) df <- data.frame( group = as.factor(rep(c("subtype1", "subtype2", "subtype3"),2)), proportion = c(1/3,1/3,1/3,1/6,1/2,1/3), label = as.factor(rep(c("condition1","condition2"),each = 3)) ) bp<- ggplot(df, aes(x=proportion,y = "", fill=group))+ geom_bar(width = 2, stat = "identity") + facet_grid(cols = vars(label)) pie <- bp + coord_polar("x", start=0) + xlab("subtype proportions") + ylab("") pie + theme(panel.background = element_rect( fill = 'white', colour = 'black'), panel.grid.minor.x = element_line(size = 0.5), panel.grid.minor.y = element_line(size = 0.5), panel.grid.major.x = element_line(size = 0.5), panel.grid.major.y = element_line(size = 0.5), panel.grid.major = element_line(colour = "grey")) ## ----echo = F----------------------------------------------------------------- x1 <- rnorm(33,10,2) x2 <- rnorm(33,10,2) x3 <- rnorm(33,20,2) x4 <- rnorm(17,10,2) x5 <- rnorm(50,10,2) x6 <- rnorm(33,20,2) df <- data.frame( group = c(rep(c("subtype1", "subtype2", "subtype3"),each = 33), c(rep("subtype1",17),rep("subtype2",50),rep("subtype3",33))), conditions = factor(c(rep(1,99),rep(2,100))), values = c(x1,x2,x3,x4,x5,x6) ) p <- ggplot(df,aes(x = conditions,y = values)) + geom_violin() + geom_jitter(aes(colour = group)) + xlab("conditions") + ylab("gene expressions") p + theme(panel.background = element_rect( fill = 'white', colour = 'black'), panel.grid.minor.x = element_line(size = 0.5), panel.grid.minor.y = element_line(size = 0.5), panel.grid.major.x = element_line(size = 0.5), panel.grid.major.y = element_line(size = 0.5), panel.grid.major = element_line(colour = "grey")) ## ----echo = F----------------------------------------------------------------- x1 <- rnorm(33,10,2) x2 <- rnorm(33,20,2) x3 <- rnorm(33,30,2) x4 <- rnorm(17,10,2) x5 <- rnorm(50,20,2) x6 <- rnorm(33,30,2) df <- data.frame( group = c(rep(c("subtype1", "subtype2", "subtype3"),each = 33), c(rep("subtype1",17),rep("subtype2",50),rep("subtype3",33))), conditions = factor(c(rep(1,99),rep(2,100))), values = c(x1,x2,x3,x4,x5,x6) ) p <- ggplot(df,aes(x = conditions,y = values)) + geom_violin() + geom_jitter(aes(colour = group)) + xlab("conditions") + ylab("gene expressions") p + theme(panel.background = element_rect( fill = 'white', colour = 'black'), panel.grid.minor.x = element_line(size = 0.5), panel.grid.minor.y = element_line(size = 0.5), panel.grid.major.x = element_line(size = 0.5), panel.grid.major.y = element_line(size = 0.5), panel.grid.major = element_line(colour = "grey")) ## ----------------------------------------------------------------------------- suppressMessages(library(scDDboost)) ## ----------------------------------------------------------------------------- data(sim_dat) ## ----------------------------------------------------------------------------- data_counts <- SummarizedExperiment::assays(sim_dat)$counts conditions <- SummarizedExperiment::colData(sim_dat)$conditions rownames(data_counts) <- seq_len(1000) ##here we use 2 cores to compute the distance matrix bp <- BiocParallel::MulticoreParam(2) D_c <- calD(data_counts,bp) ProbDD <- pdd(data = data_counts,cd = conditions, bp = bp, D = D_c) ## ----------------------------------------------------------------------------- ## determine the number of subtypes K <- detK(D_c) ## ----------------------------------------------------------------------------- EDD <- which(ProbDD > 0.95) ## ----------------------------------------------------------------------------- EDD <- getDD(ProbDD,0.05) ## ----------------------------------------------------------------------------- sessionInfo()