r - Why heatmap.2 add unwanted replicate columns? -
given data, (complete 1 can found here: http://pastebin.com/raw.php?i=6ntcnlj7):
probes gene.symbol immgen foo_yj_06.ip foo_mi_06.ip foo_nl_06.id foo_yj_06.id foo_mi_06.id bar_nn_06.ip bar_pr_06.ip bar_yj_06.ip bar_mi_06.ip bar_nl_06.id bar_yj_06.id bar_mi_06.id bar_nn_24.ip bar_pr_24.ip bar_yj_24.ip bar_mi_24.ip bar_nn_06.ip bar_nn_24.ip bar_pr_06.ip bar_pr_24.ip bar_yj_06.ip bar_yj_24.ip bar_mi_06.ip bar_mi_24.ip bar_nl_06.id bar_yj_06.id bar_mi_06.id txt_nl_06.id txt_yj_06.ip txt_mi_06.ip txt_yj_06.id txt_mi_06.id xxx_yj_06.ip xxx_mi_06.ip xxx_nl_06.id xxx_yj_06.id xxx_mi_06.id kth_nl_06.id kth_yj_06.ip kth_mi_06.ip k3_yj_06.id k3_mi_06.id uuu_yj_06.in uuu_mi_06.in dar_nl_06.id dar_yj_06.id dar_mi_06.id 1425352_at rcor3 stromalcells(12.99),dendriticcells(12.18),stemcells(11.43),nkcells(10.50),macrophages(10.11),abtcells(9.11),neutrophils(8.72),monocytes(8.63),bcells(8.61),gdtcells(7.71) 1.162 0.795 0.695 0.701 1.085 1.052 1.544 0.75 1.305 1.213 1.142 0.814 0.79 0.89 1.691 1.013 1.052 0.79 1.544 0.89 0.75 1.691 1.305 1.013 1.213 1.142 0.814 1.556 0.744 1.22 1.239 1.164 0.827 1.203 0.778 0.929 0.95 0 0.877 0.906 1.294 0.904 0 1.2 0.927 0.704 1.181 1417466_at rgs5 stromalcells(72.03),neutrophils(3.39),dendriticcells(3.31),nkcells(3.28),monocytes(3.25),macrophages(3.15),gdtcells(3.01),abtcells(2.99),bcells(2.80),stemcells(2.80) 1.149 0.904 1.225 0.821 1.075 0.947 0.969 1.262 0.868 1.013 0.984 0.938 0.925 1.11 1.36 1.014 0.947 0.925 0.969 1.11 1.262 1.36 0.868 1.014 1.013 0.984 0.938 0.877 0.887 1.035 1.226 0.979 1.142 1.126 0.933 0.854 1.033 0.911 1.255 1.038 1.125 1.086 1.18 0.958 1.115 1.017 1.061 i obtain heatmap, shown tail. note added unwanted replicated columns (marked red box).
for example bar_yj_06.ip appear once in data above. in plot appear twice bar_yj_06.ip , bar_yj_06.ip.1
why that? hand how can remove them?
this code use generate above figure:
#!/usr/bin/env rscript library(gplots); library(rcolorbrewer); plot_hclust <- function(inputfile,clust.height,type.order=c(),row.margins=30) { dat.bcd <- read.table(inputfile,na.strings=na, sep="\t",header=true); base <- substr(basename(inputfile), 1, nchar(basename(inputfile)) - 4 ) rownames(dat.bcd) <- do.call(paste,c(dat.bcd[c("probes","gene.symbol","immgen")],sep=" ")) dat.bcd <- dat.bcd[,!names(dat.bcd) %in% c("probes","gene.symbol","immgen")] dat.bcd <- dat.bcd # clustering , distance function hclustfunc <- function(x) hclust(x, method="complete") distfunc <- function(x) dist(x,method="maximum") # select based on fc, long of them >= anylim anylim <- 2.0 dat.bcd <- dat.bcd[ apply(dat.bcd, 1,function(x) (x >= anylim)), ] nrow(dat.bcd); #print(heatout): # clustering functions height <- clust.height; # define output file name heatout <- paste("myheatmap.pdf",sep=""); print(heatout) # compute distance , clusteirn function d.bcd <- distfunc(dat.bcd) fit.bcd <- hclustfunc(d.bcd) # plot hierarchical dendogram without heatmap # cluster height #cutree , rect.huclust has used in tandem clusters <- cutree(fit.bcd, h=height) nofclust.height <- length(unique(as.vector(clusters))); myorder <- colnames(dat.bcd); if (length(type.order)>0) { myorder <- type.order } # define colors #hmcols <- rev(brewer.pal(11,"spectral")); hmcols <- rev(redgreen(2750)); selcol <- colorramppalette(brewer.pal(12,"set3")) selcol2 <- colorramppalette(brewer.pal(9,"set1")) sdcol= selcol(5); clustcol.height = selcol2(nofclust.height); # plot heatmap pdf(file=heatout,width=50,height=80); par(xaxs="i"); # bi-clustering heatmap.2(as.matrix(dat.bcd), trace='none', dendrogram='both',colv=t, scale='row', hclust=hclustfunc, distfun=distfunc, col=hmcols, symbreak=t, margins=c(15,200), keysize=0.5, labrow=rownames(dat.bcd), lwid=c(2,0.1,4), lhei=c(0.05,3), lmat=rbind(c(5,0,4),c(3,1,2)), rowsidecolors=clustcol.height[clusters]) dev.off(); } # plotting plot_hclust("http://pastebin.com/raw.php?i=6ntcnlj7",clust.height=3);
this not heatmap.2 issue. of duplicated samples appear in source data frame. should review workflow , fix step @ duplicates got introduced data.
alternative ad hoc solution remove duplicated columns data frame before plotting heatmap:
data <- read.table(file='http://pastebin.com/raw.php?i=6ntcnlj7', header=t) # obtain logical vector (true/false), true == duplicated elements ind <- duplicated(t(data)) # retain unique columns # ! == inverts logical vector, true == unique elements subset <- data[,!ind]
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