plotPCPApp {bigPint} | R Documentation |
Plot interactive parallel coordinate plots.
plotPCPApp(data = data, pointColor = "orange")
data |
DATA FRAME | Read counts for parallel coordinate lines |
pointColor |
CHARACTER STRING | Color of overlaid points on scatterplot matrix; default "orange" |
A Shiny application that shows a parallel coordinate plot and allows users to draw rectangular areas across samples and remove genes that are not inside these areas. The user can download a file that contains the gene IDs that remain.
# Example: Create interactive parallel coordinate plot for genes that have # FDR < 0.01 and logFC < -4. Standardize genes to have an average of zero # and a standard deviation of one. data(soybean_ir_sub) data(soybean_ir_sub_metrics) # Create standardized version of data library(matrixStats) soybean_ir_sub_st = as.data.frame(t(apply(as.matrix(soybean_ir_sub[,-1]), 1, scale))) soybean_ir_sub_st$ID = as.character(soybean_ir_sub$ID) soybean_ir_sub_st = soybean_ir_sub_st[,c(length(soybean_ir_sub_st), 1:length(soybean_ir_sub_st)-1)] colnames(soybean_ir_sub_st) = colnames(soybean_ir_sub) nID = which(is.nan(soybean_ir_sub_st[,2])) soybean_ir_sub_st[nID,2:length(soybean_ir_sub_st)] = 0 library(dplyr, warn.conflicts = FALSE) plotGenes = filter(soybean_ir_sub_metrics[["N_P"]], FDR < 0.01, logFC < -4) %>% select(ID) pcpDat = filter(soybean_ir_sub_st, ID %in% plotGenes[,1]) app <- plotPCPApp(data = pcpDat, pointColor = "purple") if (interactive()) { shiny::runApp(app, display.mode = "normal") }