view tools/myTools/bin/.Rhistory @ 1:7e5c71b2e71f draft default tip

Uploaded

}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
View(isdisc)
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings$hammingdist<-apply(isdisc,1,function(x) sum(disc != x))
View(hammings)
is<-read.delim("internal_markers.txt",sep=" ")
is$ID<-paste(is$replicate,is$perturbation,sep="_")
row.names(is)<-is$ID
is<- is %>% select(-ID,-perturbation,-replicate)
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(row.names(isdisc))
colnames(hammings)=c("perturbations")
# hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
# colnames(hammings)=c("replicate","perturbation")
hammings<-data.frame(row.names())
hammings$hammingdist<-apply(isdisc,1,function(x) sum(disc != x))
View(hammings)
is<-read.delim("internal_markers.txt",sep=" ")
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
# hammings<-data.frame(row.names())
test$hammingdist<-apply(isdisc,1,function(x) sum(disc != x))
# hammings<-data.frame(row.names(isdisc))
# colnames(hammings)=c("perturbations")
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
# hammings<-data.frame(row.names(isdisc))
# colnames(hammings)=c("perturbations")
test<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(test)=c("replicate","perturbation")
# hammings<-data.frame(row.names())
test$hammingdist<-apply(isdisc,1,function(x) sum(disc != x))
View(test)
# hammings<-data.frame(row.names(isdisc))
# colnames(hammings)=c("perturbations")
test<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(test)=c("replicate","perturbation")
# hammings<-data.frame(row.names())
test$hammingdist<-apply(isdisc[,3],1,function(x) sum(disc != x))
# hammings<-data.frame(row.names())
test$hammingdist<-lapply(isdisc[,3],1,function(x) sum(disc != x))
# hammings<-data.frame(row.names())
test$hammingdist<-lapply(isdisc[,3],function(x) sum(disc != x))
hammings$hammingdist<-apply(isdisc,1,function(x) sum(disc != x))
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
exp<-read.delim('exp_internalmarkers.txt',sep=" ",row.names = 1)
samples<-read.delim("test-data/samples.txt",sep="\t",row.names = 1)
exp<-exp %>% dplyr::filter(row.names(exp) %in% row.names(samples))
desired<-"sensitive"
undesired<-"resistant"
filter<-"strict"
dfdes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% desired,,drop=FALSE]))
meandes<- apply(dfdes,2,mean)
dfundes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% undesired,,drop=FALSE]))
meandundes<-apply(dfundes,2,mean)
test<-meandes-meandundes
disc<-test
disc[disc<0]<-0
disc[disc>0]<-1
nodes<-colnames(dfdes)
is<-read.delim("internal_markers.txt",sep=" ")
is$ID<-paste(is$replicate,is$perturbation,sep="_")
row.names(is)<-is$ID
is<- is %>% select(-ID,-perturbation,-replicate)
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings$hammingdist<-lapply(isdisc[,3],function(x) sum(disc != x))
#plyr::count(hammings$hammingdist)
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
poi<-Reduce(intersect,list(hams1_1$perturbations))
write.table(poi,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,col.names = c('pert'))
write.table(poi,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
exp<-read.delim('exp_internalmarkers.txt',sep=" ",row.names = 1)
samples<-read.delim("test-data/samples.txt",sep="\t",row.names = 1)
exp<-exp %>% dplyr::filter(row.names(exp) %in% row.names(samples))
desired<-"sensitive"
undesired<-"resistant"
filter<-"strict"
dfdes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% desired,,drop=FALSE]))
meandes<- apply(dfdes,2,mean)
dfundes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% undesired,,drop=FALSE]))
meandundes<-apply(dfundes,2,mean)
test<-meandes-meandundes
disc<-test
disc[disc<0]<-0
disc[disc>0]<-1
nodes<-colnames(dfdes)
is<-read.delim("internal_markers.txt",sep=" ")
is$ID<-paste(is$replicate,is$perturbation,sep="_")
row.names(is)<-is$ID
is<- is %>% select(-ID,-perturbation,-replicate)
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings$hammingdist<-lapply(isdisc[,3],function(x) sum(disc != x))
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
exp<-read.delim('exp_internalmarkers.txt',sep=" ",row.names = 1)
samples<-read.delim("test-data/samples.txt",sep="\t",row.names = 1)
exp<-exp %>% dplyr::filter(row.names(exp) %in% row.names(samples))
desired<-"sensitive"
undesired<-"resistant"
filter<-"strict"
dfdes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% desired,,drop=FALSE]))
meandes<- apply(dfdes,2,mean)
dfundes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% undesired,,drop=FALSE]))
meandundes<-apply(dfundes,2,mean)
test<-meandes-meandundes
disc<-test
disc[disc<0]<-0
disc[disc>0]<-1
nodes<-colnames(dfdes)
is<-read.delim("internal_markers.txt",sep=" ")
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings$hammingdist<-lapply(isdisc[,3],function(x) sum(disc != x))
#plyr::count(hammings$hammingdist)
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
poi<-Reduce(intersect,list(hams1_1$perturbations))
write.table(poi,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
View(hammings)
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
View(hams1_1)
poi<-Reduce(intersect,list(hams1_1$perturbations))
write.table(poi,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
source('~/Dropbox/NETISCE_galaxy/new_bin/crit2-update.R')
exp<-read.delim('exp_internalmarkers.txt',sep=" ",row.names = 1)
samples<-read.delim("test-data/samples.txt",sep="\t",row.names = 1)
exp<-exp %>% dplyr::filter(row.names(exp) %in% row.names(samples))
desired<-"sensitive"
undesired<-"resistant"
filter<-"strict"
dfdes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% desired,,drop=FALSE]))
meandes<- apply(dfdes,2,mean)
dfundes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% undesired,,drop=FALSE]))
meandundes<-apply(dfundes,2,mean)
test<-meandes-meandundes
disc<-test
disc[disc<0]<-0
disc[disc>0]<-1
nodes<-colnames(dfdes)
is<-read.delim("internal_markers.txt",sep=" ")
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings$hammingdist<-lapply(isdisc[,3],function(x) sum(disc != x))
#plyr::count(hammings$hammingdist)
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
poi<-Reduce(intersect,list(hams1_1$perturbations))
write.table(poi,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
View(hams1_1)
View(hams1_1)
poi<-Reduce(intersect,list(hams1_1$perturbations))
poi<-hams1_1
View(poi)
write.table(poi,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
write.table(hams1_1,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
View(hams1_1)
write.table(hams1_1,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
write.table(as.dataframe(hams1_1),'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
View(hams1_1)
View(hams1_1)
write.table(hams1_1,file='crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
class(hams1_1)
.libPaths('~/R_libs_36')
args = commandArgs(trailingOnly=TRUE)
library(plyr)
library(dplyr)
library(ggplot2)
library(reshape2)
library(readr)
getwd()
exp<-read.delim('exp_internalmarkers.txt',sep=" ",row.names = 1)
samples<-read.delim("test-data/samples.txt",sep="\t",row.names = 1)
exp<-exp %>% dplyr::filter(row.names(exp) %in% row.names(samples))
desired<-"sensitive"
undesired<-"resistant"
filter<-"strict"
dfdes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% desired,,drop=FALSE]))
meandes<- apply(dfdes,2,mean)
dfundes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% undesired,,drop=FALSE]))
meandundes<-apply(dfundes,2,mean)
test<-meandes-meandundes
disc<-test
disc[disc<0]<-0
disc[disc>0]<-1
nodes<-colnames(dfdes)
is<-read.delim("internal_markers.txt",sep=" ")
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings$hammingdist<-lapply(isdisc[,3],function(x) sum(disc != x))
#plyr::count(hammings$hammingdist)
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
poi<-Reduce(intersect,list(hams1_1$perturbations))
write.table(poi,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
poi<-Reduce(intersect,list(hams1_1$perturbations))
View(hams1_1)
write.table(hams1_1,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE)
write.delim(hams1_1,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,sep=" ")
write.table(hams1_1,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,sep=" ")
#!/usr/bin/env Rscript
.libPaths('~/R_libs_36')
args = commandArgs(trailingOnly=TRUE)
library(plyr)
library(dplyr)
library(reshape2)
library(readr)
getwd()
exp<-read.delim('exp_internalmarkers.txt',sep=" ",row.names = 1)
samples<-read.delim("test-data/samples.txt",sep="\t",row.names = 1)
exp<-exp %>% dplyr::filter(row.names(exp) %in% row.names(samples))
desired<-"sensitive"
undesired<-"resistant"
filter<-"strict"
dfdes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% desired,,drop=FALSE]))
meandes<- apply(dfdes,2,mean)
dfundes<- exp %>% filter(rownames(exp) %in% rownames(samples[samples$phenotype %in% undesired,,drop=FALSE]))
meandundes<-apply(dfundes,2,mean)
test<-meandes-meandundes
disc<-test
disc[disc<0]<-0
disc[disc>0]<-1
nodes<-colnames(dfdes)
is<-read.delim("internal_markers.txt",sep=" ")
isdisc<-is
if (filter=="strict"){
for (node in nodes){
if (disc[node]==0){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=min(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}else { #filter=="relaxed"
for (node in nodes){
if (disc[node]==0){
val=min(dfundes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
}
if (disc[node]==1){
val=max(dfdes[,node])
isdisc[,node]<-replace(isdisc[,node],is[,node]>val, 1)
isdisc[,node]<-replace(isdisc[,node],is[,node]<val, 0)
}
}
}
hammings<-data.frame(isdisc$replicate,isdisc$perturbation)
colnames(hammings)=c("replicate","perturbation")
hammings$hammingdist<-lapply(isdisc[,3],function(x) sum(disc != x))
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
View(hams1_1)
class(hams1_1)
write.table(hams1_1,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,sep=" ")
typeof(hams1_1$replicate)
typeof(hams1_1$perturbation)
?lapply
hammings$hammingdist<-lapply(simplify=T,isdisc[,3],function(x) sum(disc != x))
hammings$hammingdist<-sapply(isdisc[,3],function(x) sum(disc != x))
if (length(nodes)<10){
hams1_1<-hammings %>%filter(hammingdist<1)
}else{
hams1_1<-hammings %>%filter(hammingdist<=length(nodes)-round(.9*length(nodes)))
}
write.table(hams1_1,'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,sep=" ")
write.table(hams1_1[c(1,2),],'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,sep=" ")
View(hams1_1)
View(hams1_1)
write.table(hams1_1[c(1,2),],'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,sep=" ")
write.table(hams1_1[,c(1,2)],'crit2_perturbations.txt',quote=FALSE,row.names = FALSE,sep=" ")