In piotrsobecki/rdmdecon: Deconvolution based on Roadmap data

knitr::opts_chunk$set(echo = TRUE,error=TRUE,warnings=FALSE)

plotRes <- function(res){
  res_trimmed = res[which(rowMeans(res,na.rm = TRUE) >= 0.01 ),]
  boxplot(t(res_trimmed),xlab="Tissue", ylab="Proportions",main="Estimated proportions",las=2,cex.axis=0.50)
}

library(rdmdeconv)
#Make signatures based on 4 proportions
signatures4 = make_signatures(proportions4_fben)

markers_df <- extract_markers2(signatures4)

markers_df_1 = markers_df[markers_df$Max==1,]
markers_df_1 = markers_df_1[order(markers_df_1$Value),]

head(markers_df)



#Deconvolution with markers lsfit method
res <- deconv(epigenomes57.N,signatures4,markers=markers_df_1$id)
plotRes(res)

piotrsobecki/rdmdecon documentation built on May 25, 2019, 7:14 a.m.