R/utility.script.R

In lehallib/DEswan: Differential Expression Sliding Window ANalaysis

# # utility script for trajectory analysis as in Lehallier et al 2019, Nature medicine
# 
# rm(list=ls())
# 
# require("DEswan")
# # devtools::install_github("lehallib/DEswan",build_vignettes = T)
# 
# data=DEswan::agingplasmaproteome[,-c(1:3)]
# dataSupp=DEswan::agingplasmaproteome[,c(1:3)]
# 
# plx.tot=NULL
# x=dataSupp$Age
# i=1
# 
# plx.tot=NULL
# for(i in 1:ncol(data)){
#   y=as.vector(scale(data[,i]))
#   xy=data.frame(na.omit(cbind(x=x,y=y)))
#   xy=xy[order(xy$x),]
#   plx<-predict(loess(xy$y~xy$x),newdata = min(x):max(x), se=T)
#   plx.tot=rbind(plx.tot,plx$fit)
#   print(i)
# }
# 
# colnames(plx.tot)<-paste("X_",min(x):max(x),sep="")
# rownames(plx.tot)<-colnames(data)
# head(plx.tot)
# 
# 
# require(gplots)
# pairs.breaks <- seq(-1, 1, by=0.01)
# mycol <- colorpanel(n=length(pairs.breaks)-1,low="deepskyblue",mid="black",high="yellow")
# require(gplots)
# toHeatmap=plx.tot
# 
# 
#   # modify margins plot
#   par(oma=c(1.1, # bottom
#             2.1, # left
#             2.1, # top
#             5.1)) # right
#   
#   hm=(heatmap.2(as.matrix(toHeatmap),
#                 cexRow=.01,cexCol=1,
#                 trace="none",
#                 dendrogram="both",
#                 breaks=pairs.breaks, 
#                 col=mycol, 
#                 Rowv=T,key=F,
#                 Colv=F,
#                 lhei=c(0.2,10),
#                 lwid=c(.2,3)
#   ))
#   
#   
#   
#   
#   
#   
#   # make clustering and generate files for different cutoffs
#   hc=hclust(dist(as.matrix(plx.tot)))
#   
# 
#   hc.list=list()
#   jjj=5
#   for(jjj in c(2:20)){
#     x.ct=mean(c(sort(hc$height,decreasing = T)[jjj-1],sort(hc$height,decreasing = T)[jjj]))
#     ct=cutree(hc, h = x.ct)
#     hc.list[[jjj]]<-ct
#   }
#