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Copy path200730_probs_mixall_breast_lvl3.R
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200730_probs_mixall_breast_lvl3.R
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library(cmapR)
library(umap)
library(ranger)
library(pbapply)
pboptions(type="timer")
# prepping data ----
# ^ common ligands from breast samples only ----
if (file.exists("~/Dropbox/GDB_archive/CMapCorr_files/200730_lvl3_breastonly.RData")) {
load("~/Dropbox/GDB_archive/CMapCorr_files/200730_lvl3_breastonly.RData")
} else {
if (exists("lvl3_data")) {
} else if (file.exists("~/Dropbox/GDB_archive/CMapCorr_files/lvl3_inputs.RData")) {
load("~/Dropbox/GDB_archive/CMapCorr_files/lvl3_inputs.RData")
} else {
source("lvl3_inputs.R")
}
ctBR <- ct14[grepl("breast_",names(ct14))]
rm(lig16,ct14)
temp_cdesc <- lvl3_data@cdesc[lvl3_data@cdesc$cell_id %in% ctBR,]
lig29 <- Reduce(intersect,tapply(temp_cdesc$pert_iname,temp_cdesc$cell_id,c))
temp_cdesc <- temp_cdesc[temp_cdesc$pert_iname %in% lig29,]
temp_cdesc_ctrl <- lvl3_data_ctl@cdesc[lvl3_data_ctl@cdesc$rna_plate %in% unique(temp_cdesc$rna_plate),]
BRmat <- cbind(lvl3_data@mat[,rownames(temp_cdesc)],
lvl3_data_ctl@mat[,rownames(temp_cdesc_ctrl)])
BRcdesc <- rbind(temp_cdesc,temp_cdesc_ctrl)
save(BRmat,BRcdesc,lig29,ctBR,file="~/Dropbox/GDB_archive/CMapCorr_files/200730_lvl3_breastonly.RData")
}
# ^ UMAP ----
if (!file.exists("~/Dropbox/GDB_archive/CMapCorr_files/200730_lvl3_breastonly_umap.RData")) {
temp_param <- umap.defaults
temp_param$n_neighbors <- 30
temp_param$metric <- "cosine"
temp_param$min_dist <- 0.2
temp_param$n_epochs <- 500
BRumap <- umap(t(BRmat),config=temp_param)
save(BRumap,file="~/Dropbox/GDB_archive/CMapCorr_files/200730_lvl3_breastonly_umap.RData")
}
# load("~/Dropbox/GDB_archive/CMapCorr_files/200730_lvl3_breastonly_umap.RData")
# Z <- sample(nrow(BRumap$layout))
# par(mar=c(1.5,1,1,0.5),mgp=c(0,0,0))
# plot(BRumap$layout[Z,],pch=20,
# col=qualitative_hcl(6,palette="dark3",alpha=0.5)[as.factor(BRcdesc$cell_id[Z])],
# xaxt="n",yaxt="n",main="Coloured by cell type",xlab="UMAP1",ylab="UMAP2")
# plot(BRumap$layout[Z,],pch=20,
# col=c(qualitative_hcl(29,palette="dark3",alpha=0.5),
# "black","black")[factor(BRcdesc$pert_iname[Z],levels=c(lig29,"H2O","PBS"))],
# xaxt="n",yaxt="n",main="Coloured by ligand",xlab="UMAP1",ylab="UMAP2")
# temp_plate <- as.factor(BRcdesc$rna_plate)
# plot(BRumap$layout[Z,],pch=20,
# col=qualitative_hcl(length(levels(temp_plate)),palette="dark3",alpha=0.5)[temp_plate[Z]],
# xaxt="n",yaxt="n",main="Coloured by cell type",xlab="UMAP1",ylab="UMAP2")
# ^ No cell line balancing ----
scores_nobal <- list()
for (LIG in lig29) {
print(paste0(which(lig29 == LIG),"/",length(lig29)))
testIDs_true <- rownames(BRcdesc)[BRcdesc$pert_iname == LIG]
scores_nobal[[LIG]] <- pbsapply(seq_along(testIDs_true),function(X){
trainIDs_true <- testIDs_true[-X]
trainIDs_false <- sample(setdiff(rownames(BRcdesc),testIDs_true),
length(trainIDs_true))
# table(BRcdesc[trainIDs_true,c("pert_iname","cell_id")])
# addmargins(table(BRcdesc[trainIDs_false,c("pert_iname","cell_id")]))
# plot(BRumap$layout[Z,],pch=20,
# col=qualitative_hcl(6,palette="dark3",alpha=0.5)[as.factor(BRcdesc$cell_id[Z])],
# xaxt="n",yaxt="n",main="Coloured by cell type",xlab="UMAP1",ylab="UMAP2")
# rect(par("usr")[1],par("usr")[3],par("usr")[2],par("usr")[4],col=scales::alpha("white",.7))
# points(BRumap$layout[trainIDs_true,],pch=".",cex=2,col="dodgerblue")
# points(BRumap$layout[trainIDs_false,],pch=".",cex=2,col="red")
trainIDs <- sample(c(trainIDs_false,trainIDs_true))
rfmodel <- ranger(x=t(BRmat[,trainIDs]),
y=BRcdesc[trainIDs,"pert_iname"] == LIG,
num.threads=8,num.trees=1e3,probability=T,
verbose=F)
testIDs <- setdiff(colnames(BRmat),trainIDs)
testResults <- predict(rfmodel,
t(BRmat[,testIDs]))
temp_train <- as.data.frame(rfmodel$predictions[,which(colnames(rfmodel$predictions) == "TRUE")])
rownames(temp_train) <- trainIDs
colnames(temp_train) <- "score"
temp_train$source <- "train"
temp_train$label <- BRcdesc[trainIDs,"pert_iname"] == LIG
temp_test <- as.data.frame(testResults$predictions[,which(colnames(rfmodel$predictions) == "TRUE")])
rownames(temp_test) <- testIDs
colnames(temp_test) <- "score"
temp_test$source <- "test"
temp_test$label <- BRcdesc[testIDs,"pert_iname"] == LIG
temp <- rbind(temp_train,temp_test)
return(temp[rownames(BRcdesc),])
},simplify=F)
}
save(scores_nobal,file="~/Dropbox/GDB_archive/CMapCorr_files/200730_probs_mixall_breast_lvl3_nobal.RData")