## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo=TRUE) ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- library(grid) library(matrixStats) library(ggplot2) library(bigPint) data("soybean_ir_sub") data("soybean_ir_sub_metrics") soybean_ir_sub[,-1] <- log(soybean_ir_sub[,-1]+1) nrow(soybean_ir_sub) length(which(soybean_ir_sub_metrics[["N_P"]]$FDR < 1e-7)) ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- colList = c("#00A600FF", rainbow(5)[c(1,4,5)]) ret <- plotClusters(data=soybean_ir_sub, dataMetrics = soybean_ir_sub_metrics, nC=4, colList = colList, clusterAllData = FALSE, threshVal = 1e-7, saveFile = FALSE) names(ret) grid.draw(ret[["N_P_4"]]) ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- ret <- plotClusters(data=soybean_ir_sub, dataMetrics = soybean_ir_sub_metrics, nC=4, colList = colList, clusterAllData = TRUE, threshVal = 1e-7, saveFile = FALSE) grid.draw(ret[["N_P_4"]]) ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- ret <- plotClusters(data=soybean_ir_sub, nC=4, colList = colList, clusterAllData = TRUE, saveFile = FALSE) grid.draw(ret[["N_P_4"]]) ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- data(soybean_cn_sub) data(soybean_cn_sub_metrics) soybean_cn_sub_st <- as.data.frame(t(apply(as.matrix(soybean_cn_sub[,-1]), 1, scale))) soybean_cn_sub_st$ID <- as.character(soybean_cn_sub$ID) soybean_cn_sub_st <- soybean_cn_sub_st[,c(length(soybean_cn_sub_st), 1:length(soybean_cn_sub_st)-1)] colnames(soybean_cn_sub_st) <- colnames(soybean_cn_sub) nID <- which(is.nan(soybean_cn_sub_st[,2])) soybean_cn_sub_st[nID,2:length(soybean_cn_sub_st)] <- 0 ret <- plotClusters(data=soybean_cn_sub_st, dataMetrics = soybean_cn_sub_metrics, nC=4, colList = c("#00A600FF", "#CC00FFFF", "red", "darkorange"), lineSize = 0.5, lineAlpha = 1, clusterAllData = FALSE, aggMethod = "average", yAxisLabel = "Standardized read count", saveFile = FALSE) names(ret) grid.draw(ret[["S1_S2_4"]]) grid.draw(ret[["S1_S3_4"]]) ## ---- eval=FALSE, include=TRUE, message=FALSE, warning=FALSE------------------ # plotClusters(data=soybean_cn_sub_st, dataMetrics = soybean_cn_sub_metrics, nC=4, # colList = c("#00A600FF", "#CC00FFFF", "red", "darkorange"), lineSize = 0.5, # lineAlpha = 1, clusterAllData = FALSE, aggMethod = "average", # yAxisLabel = "Standardized read count", verbose = TRUE) ## ---- eval=TRUE, include=FALSE, message=FALSE, warning=FALSE------------------ S1S3Cluster1 <- c("Glyma18g00690.1", "Glyma08g44110.1", "Glyma01g26570.1", "Glyma07g09700.1", "Glyma02g40610.1", "Glyma17g17970.1", "Glyma19g26250.1", "Glyma10g34630.1", "Glyma14g14220.1", "Glyma19g26710.1", "Glyma03g29150.1", "Glyma08g19245.1", "Glyma07g01730.2", "Glyma18g25845.1", "Glyma08g22380.1", "Glyma20g30460.1", "Glyma12g10960.1", "Glyma16g08810.1", "Glyma18g42630.2") ## ---- eval=TRUE, include=FALSE, message=FALSE, warning=FALSE------------------ S1S3Cluster2 <- c("Glyma06g12670.1", "Glyma12g32460.1", "Glyma17g09850.1", "Glyma18g52920.1", "Glyma01g24710.1", "Glyma04g39880.1", "Glyma05g27450.2") ## ---- eval=TRUE, include=FALSE, message=FALSE, warning=FALSE------------------ S1S3Cluster3 <- c("Glyma04g37510.1", "Glyma03g19880.1") ## ---- eval=TRUE, include=FALSE, message=FALSE, warning=FALSE------------------ S1S3Cluster4 <- c("Glyma08g11570.1", "Glyma08g19290.1") ## ---- eval=FALSE, include=TRUE, message=FALSE, warning=FALSE------------------ # S1S3Cluster1 <- readRDS(paste0(tempdir(), "/S1_S3_4_1.rds")) ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- S1S3Cluster1 ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- ret <- plotSM(data = soybean_cn_sub_st, geneList = S1S3Cluster1, pointColor = "#00A600FF", saveFile = FALSE) ret[["S1_S3"]] + ggtitle("Cluster 1 Genes (n=19)") ## ---- eval=FALSE, include=TRUE, message=FALSE, warning=FALSE------------------ # S1S3Cluster2 <- readRDS(paste0(tempdir(), "/S1_S3_4_2.rds")) # S1S3Cluster3 <- readRDS(paste0(tempdir(), "/S1_S3_4_3.rds")) # S1S3Cluster4 <- readRDS(paste0(tempdir(), "/S1_S3_4_4.rds")) ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- S1S3Cluster2 S1S3Cluster3 S1S3Cluster4 ## ---- eval=TRUE, include=TRUE, message=FALSE, warning=FALSE------------------- ret <- plotClusters(data=soybean_cn_sub_st, geneLists = list(S1S3Cluster2, S1S3Cluster3, S1S3Cluster4), lineAlpha = 1, lineSize = 0.5) grid.draw(ret[["S1_S3_3"]])