BiocManager::install("BioTIP")
library(BioTIP)
library(cluster)
library(GenomicRanges)
library(Hmisc)
library(MASS)
require(stringr)
require(psych)
require(igraph)
bok<- read.csv("bok.csv")
dim(bok)  
row.names(bok)<- bok$ID_REF
book <- bok[,-1]
dim(book)
book
cli<- read.csv("pje2.csv")
cli = data.frame(cli)
cli
cli[,"cell-type:ch1"] = str_split_fixed(cli$characteristics_ch1.1,": ",2)[,2]
cli[,"Ig clonality:ch1"] = str_split_fixed(cli$characteristics_ch1.3,": ",2)[,2]
colnames(cli)[colnames(cli) == "cell-type:ch1"] = "group"
cli$Row.names = cli[,1]
head(cli[,1:3])
df <- log2(book+1)
head(df[,1:6])
samplesL <- split(cli[,"geo_accession"],f = cli$group)
lapply(samplesL, length)
test <- sd_selection(df, samplesL,0.05)
head(test[["dry"]])
igraphL <- getNetwork(test)
cluster <- getCluster_methods(igraphL)
names(cluster)
membersL_noweight <- getMCI(cluster,test)
plotBar_MCI(membersL_noweight,ylim = c(0,6))
maxMCIms <- getMaxMCImember(membersL_noweight[[1]],membersL_noweight[[2]],min =10)
names(maxMCIms)
names(maxMCIms[[1]])
names(maxMCIms[[2]])
head(maxMCIms[['idx']])
head(maxMCIms[['members']][['ABA']])