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TCGA_matched_pair_analysis.R
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TCGA_matched_pair_analysis.R
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library(here)
folder <- paste0("Results/TCGA paired data results May 2020")
for (i in c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")) {
assign(paste0("res.", i),
readRDS(here(folder, paste0("results.TCGA.paired_", i, ".rds"))))
assign(paste0("pvals.", i),
as.data.frame(
get(paste0("res.", i))[c(2,3,4,8,9,12,14,17,19,20,23,24,27,31,32,35,36,39,43,44,47,48)]
))
assign(paste0("qvals.", i),
as.data.frame(
get(paste0("res.", i))[c(5,6,7,10,11,13,18,21,22,25,26,30,33,34,37,38,42,45,46,49,50)]
))
}
{
rownames(pvals.brca) <- gsub('\\..*', '', rownames(res.brca$counts))
rownames(pvals.kirc) <- gsub('\\..*', '', rownames(res.kirc$counts))
rownames(pvals.thca) <- gsub('\\..*', '', rownames(res.thca$counts))
rownames(pvals.luad) <- gsub('\\..*', '', rownames(res.luad$counts))
rownames(pvals.lihc) <- gsub('\\..*', '', rownames(res.lihc$counts))
rownames(pvals.lihc_long.chain) <- gsub('\\..*', '', rownames(res.lihc_long.chain$counts))
rownames(pvals.lusc) <- gsub('\\..*', '', rownames(res.lusc$counts))
rownames(pvals.prad) <- gsub('\\..*', '', rownames(res.prad$counts))
rownames(pvals.coad) <- gsub('\\..*', '', rownames(res.coad$counts))
rownames(qvals.brca) <- rownames(pvals.brca$counts)
rownames(qvals.kirc) <- rownames(pvals.kirc$counts)
rownames(qvals.thca) <- rownames(pvals.thca$counts)
rownames(qvals.luad) <- rownames(pvals.luad$counts)
rownames(qvals.lihc) <- rownames(pvals.lihc$counts)
rownames(qvals.lihc_long.chain) <- rownames(pvals.lihc_long.chain$counts)
rownames(qvals.lusc) <- rownames(pvals.lusc$counts)
rownames(qvals.prad) <- rownames(pvals.prad$counts)
rownames(qvals.coad) <- rownames(pvals.coad$counts)
}
for (i in c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")) {
assign(paste0("calls.", i),
data.frame(
get(paste0("qvals.", i)) < 0.05
))
rm(list=paste0("qvals.", i))
}
{
pvals.brca$voom_lnHM.log <- pmin(pvals.brca$p.voom, pvals.brca$p.disp.lnHM.log)
pvals.brca$voom_MDSeq.zi <- pmin(pvals.brca$p.voom, pvals.brca$p.disp.MDSeq.zi)
pvals.brca$lnHM.log_lnHM.log <- pmin(pvals.brca$p.mean.lnHM.log, pvals.brca$p.disp.lnHM.log)
pvals.kirc$voom_lnHM.log <- pmin(pvals.kirc$p.voom, pvals.kirc$p.disp.lnHM.log)
pvals.kirc$voom_MDSeq.zi <- pmin(pvals.kirc$p.voom, pvals.kirc$p.disp.MDSeq.zi)
pvals.kirc$lnHM.log_lnHM.log <- pmin(pvals.kirc$p.mean.lnHM.log, pvals.kirc$p.disp.lnHM.log)
pvals.thca$voom_lnHM.log <- pmin(pvals.thca$p.voom, pvals.thca$p.disp.lnHM.log)
pvals.thca$voom_MDSeq.zi <- pmin(pvals.thca$p.voom, pvals.thca$p.disp.MDSeq.zi)
pvals.thca$lnHM.log_lnHM.log <- pmin(pvals.thca$p.mean.lnHM.log, pvals.thca$p.disp.lnHM.log)
pvals.luad$voom_lnHM.log <- pmin(pvals.luad$p.voom, pvals.luad$p.disp.lnHM.log)
pvals.luad$voom_MDSeq.zi <- pmin(pvals.luad$p.voom, pvals.luad$p.disp.MDSeq.zi)
pvals.luad$lnHM.log_lnHM.log <- pmin(pvals.luad$p.mean.lnHM.log, pvals.luad$p.disp.lnHM.log)
pvals.lihc$voom_lnHM.log <- pmin(pvals.lihc$p.voom, pvals.lihc$p.disp.lnHM.log)
pvals.lihc$voom_MDSeq.zi <- pmin(pvals.lihc$p.voom, pvals.lihc$p.disp.MDSeq.zi)
pvals.lihc$lnHM.log_lnHM.log <- pmin(pvals.lihc$p.mean.lnHM.log, pvals.lihc$p.disp.lnHM.log)
pvals.lihc_long.chain$voom_lnHM.log <- pmin(pvals.lihc_long.chain$p.voom, pvals.lihc_long.chain$p.disp.lnHM.log)
pvals.lihc_long.chain$voom_MDSeq.zi <- pmin(pvals.lihc_long.chain$p.voom, pvals.lihc_long.chain$p.disp.MDSeq.zi)
pvals.lihc_long.chain$lnHM.log_lnHM.log <- pmin(pvals.lihc_long.chain$p.mean.lnHM.log, pvals.lihc_long.chain$p.disp.lnHM.log)
pvals.lusc$voom_lnHM.log <- pmin(pvals.lusc$p.voom, pvals.lusc$p.disp.lnHM.log)
pvals.lusc$voom_MDSeq.zi <- pmin(pvals.lusc$p.voom, pvals.lusc$p.disp.MDSeq.zi)
pvals.lusc$lnHM.log_lnHM.log <- pmin(pvals.lusc$p.mean.lnHM.log, pvals.lusc$p.disp.lnHM.log)
pvals.prad$voom_lnHM.log <- pmin(pvals.prad$p.voom, pvals.prad$p.disp.lnHM.log)
pvals.prad$voom_MDSeq.zi <- pmin(pvals.prad$p.voom, pvals.prad$p.disp.MDSeq.zi)
pvals.prad$lnHM.log_lnHM.log <- pmin(pvals.prad$p.mean.lnHM.log, pvals.prad$p.disp.lnHM.log)
pvals.coad$voom_lnHM.log <- pmin(pvals.coad$p.voom, pvals.coad$p.disp.lnHM.log)
pvals.coad$voom_MDSeq.zi <- pmin(pvals.coad$p.voom, pvals.coad$p.disp.MDSeq.zi)
pvals.coad$lnHM.log_lnHM.log <- pmin(pvals.coad$p.mean.lnHM.log, pvals.coad$p.disp.lnHM.log)
calls.brca$thr.expHMM <- pvals.brca$prob.expHMM > res.brca$thr.expHMM
calls.brca$point5.expHMM <- pvals.brca$prob.expHMM > 0.5
calls.brca$thr.lnHMM <- pvals.brca$prob.lnHMM > res.brca$thr.lnHMM
calls.brca$point5.lnHMM <- pvals.brca$prob.lnHMM > 0.5
calls.kirc$thr.expHMM <- pvals.kirc$prob.expHMM > res.kirc$thr.expHMM
calls.kirc$point5.expHMM <- pvals.kirc$prob.expHMM > 0.5
calls.kirc$thr.lnHMM <- pvals.kirc$prob.lnHMM > res.kirc$thr.lnHMM
calls.kirc$point5.lnHMM <- pvals.kirc$prob.lnHMM > 0.5
calls.thca$thr.expHMM <- pvals.thca$prob.expHMM > res.thca$thr.expHMM
calls.thca$point5.expHMM <- pvals.thca$prob.expHMM > 0.5
calls.thca$thr.lnHMM <- pvals.thca$prob.lnHMM > res.thca$thr.lnHMM
calls.thca$point5.lnHMM <- pvals.thca$prob.lnHMM > 0.5
calls.luad$thr.expHMM <- pvals.luad$prob.expHMM > res.luad$thr.expHMM
calls.luad$point5.expHMM <- pvals.luad$prob.expHMM > 0.5
calls.luad$thr.lnHMM <- pvals.luad$prob.lnHMM > res.luad$thr.lnHMM
calls.luad$point5.lnHMM <- pvals.luad$prob.lnHMM > 0.5
calls.lihc$thr.expHMM <- pvals.lihc$prob.expHMM > res.lihc$thr.expHMM
calls.lihc$point5.expHMM <- pvals.lihc$prob.expHMM > 0.5
calls.lihc$thr.lnHMM <- pvals.lihc$prob.lnHMM > res.lihc$thr.lnHMM
calls.lihc$point5.lnHMM <- pvals.lihc$prob.lnHMM > 0.5
calls.lihc_long.chain$thr.expHMM <- pvals.lihc_long.chain$prob.expHMM > res.lihc_long.chain$thr.expHMM
calls.lihc_long.chain$point5.expHMM <- pvals.lihc_long.chain$prob.expHMM > 0.5
calls.lihc_long.chain$thr.lnHMM <- pvals.lihc_long.chain$prob.lnHMM > res.lihc_long.chain$thr.lnHMM
calls.lihc_long.chain$point5.lnHMM <- pvals.lihc_long.chain$prob.lnHMM > 0.5
calls.lusc$thr.expHMM <- pvals.lusc$prob.expHMM > res.lusc$thr.expHMM
calls.lusc$point5.expHMM <- pvals.lusc$prob.expHMM > 0.5
calls.lusc$thr.lnHMM <- pvals.lusc$prob.lnHMM > res.lusc$thr.lnHMM
calls.lusc$point5.lnHMM <- pvals.lusc$prob.lnHMM > 0.5
calls.prad$thr.expHMM <- pvals.prad$prob.expHMM > res.prad$thr.expHMM
calls.prad$point5.expHMM <- pvals.prad$prob.expHMM > 0.5
calls.prad$thr.lnHMM <- pvals.prad$prob.lnHMM > res.prad$thr.lnHMM
calls.prad$point5.lnHMM <- pvals.prad$prob.lnHMM > 0.5
calls.coad$thr.expHMM <- pvals.coad$prob.expHMM > res.coad$thr.expHMM
calls.coad$point5.expHMM <- pvals.coad$prob.expHMM > 0.5
calls.coad$thr.lnHMM <- pvals.coad$prob.lnHMM > res.coad$thr.lnHMM
calls.coad$point5.lnHMM <- pvals.coad$prob.lnHMM > 0.5
calls.brca$voom_lnHM.log <- p.adjust(pvals.brca$voom_lnHM.log, method="BH") < 0.05
calls.brca$voom_MDSeq.zi <- p.adjust(pvals.brca$voom_MDSeq.zi, method="BH") < 0.05
calls.brca$lnHM.log_lnHM.log <- p.adjust(pvals.brca$lnHM.log_lnHM.log, method="BH") < 0.05
calls.kirc$voom_lnHM.log <- p.adjust(pvals.kirc$voom_lnHM.log, method="BH") < 0.05
calls.kirc$voom_MDSeq.zi <- p.adjust(pvals.kirc$voom_MDSeq.zi, method="BH") < 0.05
calls.kirc$lnHM.log_lnHM.log <- p.adjust(pvals.kirc$lnHM.log_lnHM.log, method="BH") < 0.05
calls.thca$voom_lnHM.log <- p.adjust(pvals.thca$voom_lnHM.log, method="BH") < 0.05
calls.thca$voom_MDSeq.zi <- p.adjust(pvals.thca$voom_MDSeq.zi, method="BH") < 0.05
calls.thca$lnHM.log_lnHM.log <- p.adjust(pvals.thca$lnHM.log_lnHM.log, method="BH") < 0.05
calls.luad$voom_lnHM.log <- p.adjust(pvals.luad$voom_lnHM.log, method="BH") < 0.05
calls.luad$voom_MDSeq.zi <- p.adjust(pvals.luad$voom_MDSeq.zi, method="BH") < 0.05
calls.luad$lnHM.log_lnHM.log <- p.adjust(pvals.luad$lnHM.log_lnHM.log, method="BH") < 0.05
calls.lihc$voom_lnHM.log <- p.adjust(pvals.lihc$voom_lnHM.log, method="BH") < 0.05
calls.lihc$voom_MDSeq.zi <- p.adjust(pvals.lihc$voom_MDSeq.zi, method="BH") < 0.05
calls.lihc$lnHM.log_lnHM.log <- p.adjust(pvals.lihc$lnHM.log_lnHM.log, method="BH") < 0.05
calls.lihc_long.chain$voom_lnHM.log <- p.adjust(pvals.lihc_long.chain$voom_lnHM.log, method="BH") < 0.05
calls.lihc_long.chain$voom_MDSeq.zi <- p.adjust(pvals.lihc_long.chain$voom_MDSeq.zi, method="BH") < 0.05
calls.lihc_long.chain$lnHM.log_lnHM.log <- p.adjust(pvals.lihc_long.chain$lnHM.log_lnHM.log, method="BH") < 0.05
calls.lusc$voom_lnHM.log <- p.adjust(pvals.lusc$voom_lnHM.log, method="BH") < 0.05
calls.lusc$voom_MDSeq.zi <- p.adjust(pvals.lusc$voom_MDSeq.zi, method="BH") < 0.05
calls.lusc$lnHM.log_lnHM.log <- p.adjust(pvals.lusc$lnHM.log_lnHM.log, method="BH") < 0.05
calls.prad$voom_lnHM.log <- p.adjust(pvals.prad$voom_lnHM.log, method="BH") < 0.05
calls.prad$voom_MDSeq.zi <- p.adjust(pvals.prad$voom_MDSeq.zi, method="BH") < 0.05
calls.prad$lnHM.log_lnHM.log <- p.adjust(pvals.prad$lnHM.log_lnHM.log, method="BH") < 0.05
calls.coad$voom_lnHM.log <- p.adjust(pvals.coad$voom_lnHM.log, method="BH") < 0.05
calls.coad$voom_MDSeq.zi <- p.adjust(pvals.coad$voom_MDSeq.zi, method="BH") < 0.05
calls.coad$lnHM.log_lnHM.log <- p.adjust(pvals.coad$lnHM.log_lnHM.log, method="BH") < 0.05
}
for (i in c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")) {
rm(list=c(paste0("res.", i)))
write.csv(get(paste0("calls.", i)),
here("Results/TCGA paired data results May 2020",
paste0("calls.", i, ".csv")),
row.names=row.names(get(paste0("pvals.", i))))
write.csv(get(paste0("pvals.", i)),
here("Results/TCGA paired data results May 2020",
paste0("pvals.", i, ".csv")))
}
folder <- "Data sources/Cancer-related genes"
for (i in c("brca", "kirc", "thca", "luad", "lihc",
"lusc", "prad", "coad")) {
assign(paste0("genes.", i),
readRDS(here(folder, paste0(i, "_genes_info.rds"))))
assign(paste0("dup.genes.", i),
readRDS(here(folder, paste0(i, "_genes_at_least_two_dbs_info.rds"))))
assign(paste0(i, "_related_weak"),
rownames(get(paste0("pvals.", i))) %in% get(paste0("genes.", i))$ENSEMBL)
assign(paste0(i, "_related_strong"),
rownames(get(paste0("pvals.", i))) %in% get(paste0("dup.genes.", i))$ENSEMBL)
}
rm(i, folder)
lihc_long.chain_related_weak <- lihc_related_weak
lihc_long.chain_related_strong <- lihc_related_strong
## Test ability to identify cancer-related genes with threshold using one-sided Fisher's exact test ####
tests.fisher <- names(calls.brca)
for (j in tests.fisher) {
for (i in c("brca", "kirc", "thca", "luad", "lihc",
"lusc", "prad", "coad")) {
assign(paste0("fisher.weak_", i, "_", j),
fisher.test(get(paste0(i, "_related_weak")),
get(paste0("calls.", i))[[j]],
alternative="greater")$p.val)
assign(paste0("fisher.strong_", i, "_", j),
fisher.test(get(paste0(i, "_related_strong")),
get(paste0("calls.", i))[[j]],
alternative="greater")$p.val)
}
assign(paste0("fisher.weak_lihc_long.chain_", j),
fisher.test(lihc_related_weak,
calls.lihc_long.chain[[j]],
alternative="greater")$p.val)
assign(paste0("fisher.strong_lihc_long.chain_", j),
fisher.test(lihc_related_strong,
calls.lihc_long.chain[[j]],
alternative="greater")$p.val)
}
rm(i,j)
fisher.tests.weak <- data.frame(matrix(nrow=length(tests.fisher), ncol=9))
names(fisher.tests.weak) <- c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")
rownames(fisher.tests.weak) <- tests.fisher
for (j in seq_along(rownames(fisher.tests.weak))) {
for (i in names(fisher.tests.weak)) {
fisher.tests.weak[[i]][j] <- get(paste0("fisher.weak_", i, "_", tests.fisher[j]))
rm(list=paste0("fisher.weak_", i, "_", tests.fisher[j]))
}
}
fisher.tests.strong <- data.frame(matrix(nrow=length(tests.fisher), ncol=9))
names(fisher.tests.strong) <- c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")
rownames(fisher.tests.strong) <- tests.fisher
for (j in seq_along(rownames(fisher.tests.strong))) {
for (i in names(fisher.tests.strong)) {
fisher.tests.strong[[i]][j] <- get(paste0("fisher.strong_", i, "_", tests.fisher[j]))
rm(list=paste0("fisher.strong_", i, "_", tests.fisher[j]))
}
}
rm(i,j,tests.fisher)
write.csv(fisher.tests.weak,
here("Results/TCGA paired data results May 2020",
"fisher.tests.weak_known.genes.csv"),
)
write.csv(fisher.tests.strong,
here("Results/TCGA paired data results May 2020",
"fisher.tests.strong_known.genes.csv"),
)
## Test ability to rank cancer-related genes above non-cancer-related genes using Wilcoxon rank-sum test ####
tests.ranksum <- names(pvals.brca)
for (j in tests.ranksum) {
for (i in c("brca", "kirc", "thca", "luad", "lihc",
"lusc", "prad", "coad")) {
if(grepl("prob", j)) {
assign(paste0("ranksum.weak_", i, "_", j),
wilcox.test(
rank(1 - get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_weak")) == T],
rank(1 - get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_weak")) == F],
paired=F,
alternative="less")$p.val)
assign(paste0("ranksum.strong_", i, "_", j),
wilcox.test(
rank(1 - get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_strong")) == T],
rank(1 - get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_strong")) == F],
paired=F,
alternative="less")$p.val)
} else {
assign(paste0("ranksum.weak_", i, "_", j),
wilcox.test(
rank(get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_weak")) == T],
rank(get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_weak")) == F],
paired=F,
alternative="less")$p.val)
assign(paste0("ranksum.strong_", i, "_", j),
wilcox.test(
rank(get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_strong")) == T],
rank(get(paste0("pvals.", i))[[j]])[get(paste0(i, "_related_strong")) == F],
paired=F,
alternative="less")$p.val)
}
}
rm(i)
if (grepl("prob", j)) {
assign(paste0("ranksum.weak_lihc_long.chain_", j),
wilcox.test(
rank(1 - pvals.lihc_long.chain[[j]])[lihc_related_weak == T],
rank(1 - pvals.lihc_long.chain[[j]])[lihc_related_weak == F],
paired=F,
alternative="less")$p.val)
assign(paste0("ranksum.strong_lihc_long.chain_", j),
wilcox.test(
rank(1 - pvals.lihc_long.chain[[j]])[lihc_related_strong == T],
rank(1 - pvals.lihc_long.chain[[j]])[lihc_related_strong == F],
paired=F,
alternative="less")$p.val)
} else {
assign(paste0("ranksum.weak_lihc_long.chain_", j),
wilcox.test(
rank(pvals.lihc_long.chain[[j]])[lihc_related_weak == T],
rank(pvals.lihc_long.chain[[j]])[lihc_related_weak == F],
paired=F,
alternative="less")$p.val)
assign(paste0("ranksum.strong_lihc_long.chain_", j),
wilcox.test(
rank(pvals.lihc_long.chain[[j]])[lihc_related_strong == T],
rank(pvals.lihc_long.chain[[j]])[lihc_related_strong == F],
paired=F,
alternative="less")$p.val)
}
}
rm(j)
ranksum.tests.weak <- data.frame(matrix(nrow=length(tests.ranksum), ncol=9))
names(ranksum.tests.weak) <- c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")
rownames(ranksum.tests.weak) <- tests.ranksum
for (j in seq_along(rownames(ranksum.tests.weak))) {
for (i in names(ranksum.tests.weak)) {
ranksum.tests.weak[[i]][j] <- get(paste0("ranksum.weak_", i, "_", tests.ranksum[j]))
rm(list=paste0("ranksum.weak_", i, "_", tests.ranksum[j]))
}
}
ranksum.tests.strong <- data.frame(matrix(nrow=length(tests.ranksum), ncol=9))
names(ranksum.tests.strong) <- c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")
rownames(ranksum.tests.strong) <- tests.ranksum
for (j in seq_along(rownames(ranksum.tests.strong))) {
for (i in names(ranksum.tests.strong)) {
ranksum.tests.strong[[i]][j] <- get(paste0("ranksum.strong_", i, "_", tests.ranksum[j]))
rm(list=paste0("ranksum.strong_", i, "_", tests.ranksum[j]))
}
}
rm(i,j,tests.ranksum)
write.csv(ranksum.tests.weak,
here("Results/TCGA paired data results May 2020",
"ranksum.tests.weak_known.genes.csv"),
)
write.csv(ranksum.tests.strong,
here("Results/TCGA paired data results May 2020",
"ranksum.tests.strong_known.genes.csv"),
)
## Compare methods for ability to identify cancer-related genes with threshold using McNemar's test ####
c(mcnemar.test(calls.brca$q.voom == brca_related_weak,
calls.brca$q.mean.lnHM.log == brca_related_weak)$p.val,
mean(calls.brca$q.voom == brca_related_weak),
mean(calls.brca$q.mean.lnHM.log == brca_related_weak)) # voom better
c(mcnemar.test(calls.kirc$q.voom == kirc_related_weak,
calls.kirc$q.mean.lnHM.log == kirc_related_weak)$p.val,
mean(calls.kirc$q.voom == kirc_related_weak),
mean(calls.kirc$q.mean.lnHM.log == kirc_related_weak)) # voom better
c(mcnemar.test(calls.thca$q.voom == thca_related_weak,
calls.thca$q.mean.lnHM.log == thca_related_weak)$p.val,
mean(calls.thca$q.voom == thca_related_weak),
mean(calls.thca$q.mean.lnHM.log == thca_related_weak)) # HM better
c(mcnemar.test(calls.luad$q.voom == luad_related_weak,
calls.luad$q.mean.lnHM.log == luad_related_weak)$p.val,
mean(calls.luad$q.voom == luad_related_weak),
mean(calls.luad$q.mean.lnHM.log == luad_related_weak)) # voom better
c(mcnemar.test(calls.lihc$q.voom == lihc_related_weak,
calls.lihc$q.mean.lnHM.log == lihc_related_weak)$p.val,
mean(calls.lihc$q.voom == lihc_related_weak),
mean(calls.lihc$q.mean.lnHM.log == lihc_related_weak)) # voom better
c(mcnemar.test(calls.lihc_long.chain$q.voom == lihc_related_weak,
calls.lihc_long.chain$q.mean.lnHM.log == lihc_related_weak)$p.val,
mean(calls.lihc_long.chain$q.voom == lihc_related_weak),
mean(calls.lihc_long.chain$q.mean.lnHM.log == lihc_related_weak)) # voom better
c(mcnemar.test(calls.lusc$q.voom == lusc_related_weak,
calls.lusc$q.mean.lnHM.log == lusc_related_weak)$p.val,
mean(calls.lusc$q.voom == lusc_related_weak),
mean(calls.lusc$q.mean.lnHM.log == lusc_related_weak)) # voom better
c(mcnemar.test(calls.prad$q.voom == prad_related_weak,
calls.prad$q.mean.lnHM.log == prad_related_weak)$p.val,
mean(calls.prad$q.voom == prad_related_weak),
mean(calls.prad$q.mean.lnHM.log == prad_related_weak)) # voom better
c(mcnemar.test(calls.coad$q.voom == coad_related_weak,
calls.coad$q.mean.lnHM.log == coad_related_weak)$p.val,
mean(calls.coad$q.voom == coad_related_weak),
mean(calls.coad$q.mean.lnHM.log == coad_related_weak)) # voom better
c(mcnemar.test(calls.brca$q.voom == brca_related_weak,
calls.brca$q.disp.lnHM.log == brca_related_weak)$p.val,
mean(calls.brca$q.voom == brca_related_weak),
mean(calls.brca$q.disp.lnHM.log == brca_related_weak)) # voom better
c(mcnemar.test(calls.kirc$q.voom == kirc_related_weak,
calls.kirc$q.disp.lnHM.log == kirc_related_weak)$p.val,
mean(calls.kirc$q.voom == kirc_related_weak),
mean(calls.kirc$q.disp.lnHM.log == kirc_related_weak)) # HM better
c(mcnemar.test(calls.thca$q.voom == thca_related_weak,
calls.thca$q.disp.lnHM.log == thca_related_weak)$p.val,
mean(calls.thca$q.voom == thca_related_weak),
mean(calls.thca$q.disp.lnHM.log == thca_related_weak)) # HM better
c(mcnemar.test(calls.luad$q.voom == luad_related_weak,
calls.luad$q.disp.lnHM.log == luad_related_weak)$p.val,
mean(calls.luad$q.voom == luad_related_weak),
mean(calls.luad$q.disp.lnHM.log == luad_related_weak)) # voom better
c(mcnemar.test(calls.lihc$q.voom == lihc_related_weak,
calls.lihc$q.disp.lnHM.log == lihc_related_weak)$p.val,
mean(calls.lihc$q.voom == lihc_related_weak),
mean(calls.lihc$q.disp.lnHM.log == lihc_related_weak)) # voom better
c(mcnemar.test(calls.lihc_long.chain$q.voom == lihc_related_weak,
calls.lihc_long.chain$q.disp.lnHM.log == lihc_related_weak)$p.val,
mean(calls.lihc_long.chain$q.voom == lihc_related_weak),
mean(calls.lihc_long.chain$q.disp.lnHM.log == lihc_related_weak)) # voom better
c(mcnemar.test(calls.lusc$q.voom == lusc_related_weak,
calls.lusc$q.disp.lnHM.log == lusc_related_weak)$p.val,
mean(calls.lusc$q.voom == lusc_related_weak),
mean(calls.lusc$q.disp.lnHM.log == lusc_related_weak)) # voom better
c(mcnemar.test(calls.prad$q.voom == prad_related_weak,
calls.prad$q.disp.lnHM.log == prad_related_weak)$p.val,
mean(calls.prad$q.voom == prad_related_weak),
mean(calls.prad$q.disp.lnHM.log == prad_related_weak)) # HM better
c(mcnemar.test(calls.coad$q.voom == coad_related_weak,
calls.coad$q.disp.lnHM.log == coad_related_weak)$p.val,
mean(calls.coad$q.voom == coad_related_weak),
mean(calls.coad$q.disp.lnHM.log == coad_related_weak)) # voom better
c(mcnemar.test(calls.brca$q.disp.MDSeq.zi == brca_related_weak,
calls.brca$q.disp.lnHM.log == brca_related_weak)$p.val,
mean(calls.brca$q.disp.MDSeq.zi == brca_related_weak, na.rm=T),
mean(calls.brca$q.disp.lnHM.log == brca_related_weak)) # MDSeq better
c(mcnemar.test(calls.kirc$q.disp.MDSeq.zi == kirc_related_weak,
calls.kirc$q.disp.lnHM.log == kirc_related_weak)$p.val,
mean(calls.kirc$q.disp.MDSeq.zi == kirc_related_weak, na.rm=T),
mean(calls.kirc$q.disp.lnHM.log == kirc_related_weak)) # MDSeq better
c(mcnemar.test(calls.thca$q.disp.MDSeq.zi == thca_related_weak,
calls.thca$q.disp.lnHM.log == thca_related_weak)$p.val,
mean(calls.thca$q.disp.MDSeq.zi == thca_related_weak, na.rm=T),
mean(calls.thca$q.disp.lnHM.log == thca_related_weak)) # MDSeq better
c(mcnemar.test(calls.luad$q.disp.MDSeq.zi == luad_related_weak,
calls.luad$q.disp.lnHM.log == luad_related_weak)$p.val,
mean(calls.luad$q.disp.MDSeq.zi == luad_related_weak, na.rm=T),
mean(calls.luad$q.disp.lnHM.log == luad_related_weak)) # MDSeq better
c(mcnemar.test(calls.lihc$q.disp.MDSeq.zi == lihc_related_weak,
calls.lihc$q.disp.lnHM.log == lihc_related_weak)$p.val,
mean(calls.lihc$q.disp.MDSeq.zi == lihc_related_weak, na.rm=T),
mean(calls.lihc$q.disp.lnHM.log == lihc_related_weak)) # MDSeq better
c(mcnemar.test(calls.lihc_long.chain$q.disp.MDSeq.zi == lihc_related_weak,
calls.lihc_long.chain$q.disp.lnHM.log == lihc_related_weak)$p.val,
mean(calls.lihc_long.chain$q.disp.MDSeq.zi == lihc_related_weak, na.rm=T),
mean(calls.lihc_long.chain$q.disp.lnHM.log == lihc_related_weak)) # MDSeq better
c(mcnemar.test(calls.lusc$q.disp.MDSeq.zi == lusc_related_weak,
calls.lusc$q.disp.lnHM.log == lusc_related_weak)$p.val,
mean(calls.lusc$q.disp.MDSeq.zi == lusc_related_weak, na.rm=T),
mean(calls.lusc$q.disp.lnHM.log == lusc_related_weak)) # MDSeq better
c(mcnemar.test(calls.prad$q.disp.MDSeq.zi == prad_related_weak,
calls.prad$q.disp.lnHM.log == prad_related_weak)$p.val,
mean(calls.prad$q.disp.MDSeq.zi == prad_related_weak, na.rm=T),
mean(calls.prad$q.disp.lnHM.log == prad_related_weak)) # No difference
c(mcnemar.test(calls.coad$q.disp.MDSeq.zi == coad_related_weak,
calls.coad$q.disp.lnHM.log == coad_related_weak)$p.val,
mean(calls.coad$q.disp.MDSeq.zi == coad_related_weak, na.rm=T),
mean(calls.coad$q.disp.lnHM.log == coad_related_weak)) # MDSeq better
## Compare methods on ranking of cancer-related genes using Wilcoxon signed-rank test ####
c(wilcox.test(rank(pvals.brca$p.voom)[brca_related_weak == T],
rank(pvals.brca$p.mean.lnHM.log)[brca_related_weak == T], paired=T)$p.val,
median((rank(pvals.brca$p.voom) - rank(pvals.brca$p.mean.lnHM.log))[brca_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.kirc$p.voom)[kirc_related_weak == T],
rank(pvals.kirc$p.mean.lnHM.log)[kirc_related_weak == T], paired=T)$p.val,
median((rank(pvals.kirc$p.voom) - rank(pvals.kirc$p.mean.lnHM.log))[kirc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.thca$p.voom)[thca_related_weak == T],
rank(pvals.thca$p.mean.lnHM.log)[thca_related_weak == T], paired=T)$p.val,
median((rank(pvals.thca$p.voom) - rank(pvals.thca$p.mean.lnHM.log))[thca_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.luad$p.voom)[luad_related_weak == T],
rank(pvals.luad$p.mean.lnHM.log)[luad_related_weak == T], paired=T)$p.val,
median((rank(pvals.luad$p.voom) - rank(pvals.luad$p.mean.lnHM.log))[luad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lihc$p.voom)[lihc_related_weak == T],
rank(pvals.lihc$p.mean.lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc$p.voom) - rank(pvals.lihc$p.mean.lnHM.log))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lihc_long.chain$p.voom)[lihc_related_weak == T],
rank(pvals.lihc_long.chain$p.mean.lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc_long.chain$p.voom) -
rank(pvals.lihc_long.chain$p.mean.lnHM.log))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lusc$p.voom)[lusc_related_weak == T],
rank(pvals.lusc$p.mean.lnHM.log)[lusc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lusc$p.voom) - rank(pvals.lusc$p.mean.lnHM.log))[lusc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.prad$p.voom)[prad_related_weak == T],
rank(pvals.prad$p.mean.lnHM.log)[prad_related_weak == T], paired=T)$p.val,
median((rank(pvals.prad$p.voom) - rank(pvals.prad$p.mean.lnHM.log))[prad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.coad$p.voom)[coad_related_weak == T],
rank(pvals.coad$p.mean.lnHM.log)[coad_related_weak == T], paired=T)$p.val,
median((rank(pvals.coad$p.voom) - rank(pvals.coad$p.mean.lnHM.log))[coad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.brca$p.voom)[brca_related_weak == T],
rank(pvals.brca$p.disp.lnHM.log)[brca_related_weak == T], paired=T)$p.val,
median((rank(pvals.brca$p.voom) - rank(pvals.brca$p.disp.lnHM.log))[brca_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.kirc$p.voom)[kirc_related_weak == T],
rank(pvals.kirc$p.disp.lnHM.log)[kirc_related_weak == T], paired=T)$p.val,
median((rank(pvals.kirc$p.voom) - rank(pvals.kirc$p.disp.lnHM.log))[kirc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.thca$p.voom)[thca_related_weak == T],
rank(pvals.thca$p.disp.lnHM.log)[thca_related_weak == T], paired=T)$p.val,
median((rank(pvals.thca$p.voom) - rank(pvals.thca$p.disp.lnHM.log))[thca_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.luad$p.voom)[luad_related_weak == T],
rank(pvals.luad$p.disp.lnHM.log)[luad_related_weak == T], paired=T)$p.val,
median((rank(pvals.luad$p.voom) - rank(pvals.luad$p.disp.lnHM.log))[luad_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.lihc$p.voom)[lihc_related_weak == T],
rank(pvals.lihc$p.disp.lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc$p.voom) - rank(pvals.lihc$p.disp.lnHM.log))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lihc_long.chain$p.voom)[lihc_related_weak == T],
rank(pvals.lihc_long.chain$p.disp.lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc_long.chain$p.voom) -
rank(pvals.lihc_long.chain$p.disp.lnHM.log))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lusc$p.voom)[lusc_related_weak == T],
rank(pvals.lusc$p.disp.lnHM.log)[lusc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lusc$p.voom) - rank(pvals.lusc$p.disp.lnHM.log))[lusc_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.prad$p.voom)[prad_related_weak == T],
rank(pvals.prad$p.disp.lnHM.log)[prad_related_weak == T], paired=T)$p.val,
median((rank(pvals.prad$p.voom) - rank(pvals.prad$p.disp.lnHM.log))[prad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.coad$p.voom)[coad_related_weak == T],
rank(pvals.coad$p.disp.lnHM.log)[coad_related_weak == T], paired=T)$p.val,
median((rank(pvals.coad$p.voom) - rank(pvals.coad$p.disp.lnHM.log))[coad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.brca$p.disp.MDSeq.zi)[brca_related_weak == T],
rank(pvals.brca$p.disp.lnHM.log)[brca_related_weak == T], paired=T)$p.val,
median((rank(pvals.brca$p.disp.MDSeq.zi) - rank(pvals.brca$p.disp.lnHM.log))[brca_related_weak == T])) # MD better
c(wilcox.test(rank(pvals.kirc$p.disp.MDSeq.zi)[kirc_related_weak == T],
rank(pvals.kirc$p.disp.lnHM.log)[kirc_related_weak == T], paired=T)$p.val,
median((rank(pvals.kirc$p.disp.MDSeq.zi) - rank(pvals.kirc$p.disp.lnHM.log))[kirc_related_weak == T])) # MD better
c(wilcox.test(rank(pvals.thca$p.disp.MDSeq.zi)[thca_related_weak == T],
rank(pvals.thca$p.disp.lnHM.log)[thca_related_weak == T], paired=T)$p.val,
median((rank(pvals.thca$p.disp.MDSeq.zi) - rank(pvals.thca$p.disp.lnHM.log))[thca_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.luad$p.disp.MDSeq.zi)[luad_related_weak == T],
rank(pvals.luad$p.disp.lnHM.log)[luad_related_weak == T], paired=T)$p.val,
median((rank(pvals.luad$p.disp.MDSeq.zi) - rank(pvals.luad$p.disp.lnHM.log))[luad_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.lihc$p.disp.MDSeq.zi)[lihc_related_weak == T],
rank(pvals.lihc$p.disp.lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc$p.disp.MDSeq.zi) - rank(pvals.lihc$p.disp.lnHM.log))[lihc_related_weak == T])) # MD better
c(wilcox.test(rank(pvals.lihc_long.chain$p.disp.MDSeq.zi)[lihc_related_weak == T],
rank(pvals.lihc_long.chain$p.disp.lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc_long.chain$p.disp.MDSeq.zi) -
rank(pvals.lihc_long.chain$p.disp.lnHM.log))[lihc_related_weak == T])) # MD better
c(wilcox.test(rank(pvals.lusc$p.disp.MDSeq.zi)[lusc_related_weak == T],
rank(pvals.lusc$p.disp.lnHM.log)[lusc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lusc$p.disp.MDSeq.zi) - rank(pvals.lusc$p.disp.lnHM.log))[lusc_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.prad$p.disp.MDSeq.zi)[prad_related_weak == T],
rank(pvals.prad$p.disp.lnHM.log)[prad_related_weak == T], paired=T)$p.val,
median((rank(pvals.prad$p.disp.MDSeq.zi) - rank(pvals.prad$p.disp.lnHM.log))[prad_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.coad$p.disp.MDSeq.zi)[coad_related_weak == T],
rank(pvals.coad$p.disp.lnHM.log)[coad_related_weak == T], paired=T)$p.val,
median((rank(pvals.coad$p.disp.MDSeq.zi) - rank(pvals.coad$p.disp.lnHM.log))[coad_related_weak == T])) # MD better
c(wilcox.test(rank(pvals.brca$p.voom)[brca_related_weak == T],
rank(pvals.brca$lnHM.log_lnHM.log)[brca_related_weak == T], paired=T)$p.val,
median((rank(pvals.brca$p.voom) - rank(pvals.brca$lnHM.log_lnHM.log))[brca_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.kirc$p.voom)[kirc_related_weak == T],
rank(pvals.kirc$lnHM.log_lnHM.log)[kirc_related_weak == T], paired=T)$p.val,
median((rank(pvals.kirc$p.voom) - rank(pvals.kirc$lnHM.log_lnHM.log))[kirc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.thca$p.voom)[thca_related_weak == T],
rank(pvals.thca$lnHM.log_lnHM.log)[thca_related_weak == T], paired=T)$p.val,
median((rank(pvals.thca$p.voom) - rank(pvals.thca$lnHM.log_lnHM.log))[thca_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.luad$p.voom)[luad_related_weak == T],
rank(pvals.luad$lnHM.log_lnHM.log)[luad_related_weak == T], paired=T)$p.val,
median((rank(pvals.luad$p.voom) - rank(pvals.luad$lnHM.log_lnHM.log))[luad_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.lihc$p.voom)[lihc_related_weak == T],
rank(pvals.lihc$lnHM.log_lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc$p.voom) - rank(pvals.lihc$lnHM.log_lnHM.log))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lihc_long.chain$p.voom)[lihc_related_weak == T],
rank(pvals.lihc_long.chain$lnHM.log_lnHM.log)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc_long.chain$p.voom) -
rank(pvals.lihc_long.chain$lnHM.log_lnHM.log))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lusc$p.voom)[lusc_related_weak == T],
rank(pvals.lusc$lnHM.log_lnHM.log)[lusc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lusc$p.voom) - rank(pvals.lusc$lnHM.log_lnHM.log))[lusc_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.prad$p.voom)[prad_related_weak == T],
rank(pvals.prad$lnHM.log_lnHM.log)[prad_related_weak == T], paired=T)$p.val,
median((rank(pvals.prad$p.voom) - rank(pvals.prad$lnHM.log_lnHM.log))[prad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.coad$p.voom)[coad_related_weak == T],
rank(pvals.coad$lnHM.log_lnHM.log)[coad_related_weak == T], paired=T)$p.val,
median((rank(pvals.coad$p.voom) - rank(pvals.coad$lnHM.log_lnHM.log))[coad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.brca$p.voom)[brca_related_weak == T],
rank(1 - pvals.brca$prob.lnHM)[brca_related_weak == T], paired=T)$p.val,
median((rank(pvals.brca$p.voom) - rank(1 - pvals.brca$prob.lnHM))[brca_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.kirc$p.voom)[kirc_related_weak == T],
rank(1 - pvals.kirc$prob.lnHM)[kirc_related_weak == T], paired=T)$p.val,
median((rank(pvals.kirc$p.voom) - rank(1 - pvals.kirc$prob.lnHM))[kirc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.thca$p.voom)[thca_related_weak == T],
rank(1 - pvals.thca$prob.lnHM)[thca_related_weak == T], paired=T)$p.val,
median((rank(pvals.thca$p.voom) - rank(1 - pvals.thca$prob.lnHM))[thca_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.luad$p.voom)[luad_related_weak == T],
rank(1 - pvals.luad$prob.lnHM)[luad_related_weak == T], paired=T)$p.val,
median((rank(pvals.luad$p.voom) - rank(1 - pvals.luad$prob.lnHM))[luad_related_weak == T])) # No difference
c(wilcox.test(rank(pvals.lihc$p.voom)[lihc_related_weak == T],
rank(1 - pvals.lihc$prob.lnHM)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc$p.voom) - rank(1 - pvals.lihc$prob.lnHM))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lihc_long.chain$p.voom)[lihc_related_weak == T],
rank(1 - pvals.lihc_long.chain$prob.lnHM)[lihc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lihc_long.chain$p.voom) -
rank(1 - pvals.lihc_long.chain$prob.lnHM))[lihc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.lusc$p.voom)[lusc_related_weak == T],
rank(1 - pvals.lusc$prob.lnHM)[lusc_related_weak == T], paired=T)$p.val,
median((rank(pvals.lusc$p.voom) - rank(1 - pvals.lusc$prob.lnHM))[lusc_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.prad$p.voom)[prad_related_weak == T],
rank(1 - pvals.prad$prob.lnHM)[prad_related_weak == T], paired=T)$p.val,
median((rank(pvals.prad$p.voom) - rank(1 - pvals.prad$prob.lnHM))[prad_related_weak == T])) # voom better
c(wilcox.test(rank(pvals.coad$p.voom)[coad_related_weak == T],
rank(1 - pvals.coad$prob.lnHM)[coad_related_weak == T], paired=T)$p.val,
median((rank(pvals.coad$p.voom) - rank(1 - pvals.coad$prob.lnHM))[coad_related_weak == T])) # voom better
## Assess whether DE, DD, DEDD identify different sets of cancer-related genes ####
# Informally assess whether DE and DD HMs identify different sets of cancer-related genes by plotting
# hypergeometric and Spearman correlation test p-values with alternative hypothesis that overlap and
# correlation, respectively, are lower than expected under null for sets of top-ranking genes from 1
# to all genes (or possibly for p-value threshold from 0 to 1 for hypergeometric).
for (j in c("brca", "kirc", "thca", "luad", "lihc",
"lihc_long.chain", "lusc", "prad", "coad")) {
pvals <- sort(unique(c(get(paste0("pvals.", j))$p.mean.lnHM.log, get(paste0("pvals.", j))$p.disp.lnHM.log)))
res <- data.frame(
pvals = pvals,
listA = numeric(length(pvals)),
listB = numeric(length(pvals)),
overlap = numeric(length(pvals)),
p.hyper = numeric(length(pvals)),
exp.overlap = numeric(length(pvals)),
union. = numeric(length(pvals)),
p.cor = numeric(length(pvals)),
cor = numeric(length(pvals)),
TPA = numeric(length(pvals)),
TPB = numeric(length(pvals)),
TPboth = numeric(length(pvals)),
TPAonly = numeric(length(pvals)),
TPBonly = numeric(length(pvals))
)
for (i in seq_len(length(pvals))) {
res$listA[i] <- sum(get(paste0("pvals.", j))$p.mean.lnHM.log < res$pvals[i])
res$listB[i] <- sum(get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i])
res$overlap[i] <- sum(get(paste0("pvals.", j))$p.mean.lnHM.log < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i])
res$p.hyper[i] <- phyper(res$overlap[i],
res$listA[i],
nrow(get(paste0("pvals.", j))) - res$listA[i],
res$listB[i])
res$exp.overlap[i] <- mean(get(paste0("pvals.", j))$p.mean.lnHM.log < res$pvals[i]) *
mean(get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]) * nrow(get(paste0("pvals.", j)))
res$union[i] <- sum(get(paste0("pvals.", j))$p.mean.lnHM.log < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i])
if (sum(get(paste0("pvals.", j))$p.mean.lnHM.log < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]) > 1) {
cortest <-
cor.test(get(paste0("pvals.", j))$p.mean.lnHM.log[get(paste0("pvals.", j))$p.mean.lnHM.log < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]],
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0("pvals.", j))$p.mean.lnHM.log < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]],
method="spearman", alt="less")
res$p.cor[i] <- cortest$p.val
res$cor[i] <- cortest$estimate
rm(cortest)
}
res$TPA[i] <- sum(get(paste0("pvals.", j))$p.mean.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPB[i] <- sum(get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPboth[i] <- sum(get(paste0("pvals.", j))$p.mean.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPAonly[i] <- sum(get(paste0("pvals.", j))$p.mean.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] >= res$pvals[i])
res$TPBonly[i] <- sum(get(paste0("pvals.", j))$p.mean.lnHM.log[get(paste0(j, "_related_weak"))] >= res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i])
}
assign(paste0(j, ".HM"), res)
write.csv(get(paste0(j, ".HM")),
here("Results/TCGA paired data results May 2020",
paste0(j, "_HM_mean_v_disp_known.genes.csv")),
row.names=F)
rm(pvals, res)
pvals <- sort(unique(c(get(paste0("pvals.", j))$p.mean.MDSeq.zi, get(paste0("pvals.", j))$p.disp.MDSeq.zi)))
res <- data.frame(
pvals = pvals,
listA = numeric(length(pvals)),
listB = numeric(length(pvals)),
overlap = numeric(length(pvals)),
p.hyper = numeric(length(pvals)),
exp.overlap = numeric(length(pvals)),
union. = numeric(length(pvals)),
p.cor = numeric(length(pvals)),
cor = numeric(length(pvals)),
TPA = numeric(length(pvals)),
TPB = numeric(length(pvals)),
TPboth = numeric(length(pvals)),
TPAonly = numeric(length(pvals)),
TPBonly = numeric(length(pvals))
)
for (i in seq_len(length(pvals))) {
res$listA[i] <- sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi < res$pvals[i], na.rm=T)
res$listB[i] <- sum(get(paste0("pvals.", j))$p.disp.MDSeq.zi < res$pvals[i], na.rm=T)
res$overlap[i] <- sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.MDSeq.zi < res$pvals[i], na.rm=T)
res$union[i] <- sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.MDSeq.zi < res$pvals[i], na.rm=T)
res$exp.overlap[i] <- mean(get(paste0("pvals.", j))$p.mean.MDSeq.zi < res$pvals[i], na.rm=T) *
mean(get(paste0("pvals.", j))$p.disp.MDSeq.zi < res$pvals[i], na.rm=T) * nrow(get(paste0("pvals.", j)))
res$p.hyper[i] <- phyper(res$overlap[i],
res$listA[i],
nrow(get(paste0("pvals.", j))) - res$listA[i],
res$listB[i])
if (sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.MDSeq.zi < res$pvals[i], na.rm=T) > 1) {
cortest <- cor.test(get(paste0("pvals.", j))$p.mean.MDSeq.zi[get(paste0("pvals.", j))$p.mean.MDSeq.zi < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.MDSeq.zi < res$pvals[i]],
get(paste0("pvals.", j))$p.disp.MDSeq.zi[get(paste0("pvals.", j))$p.mean.MDSeq.zi < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.MDSeq.zi < res$pvals[i]],
method="spearman", alt="less")
res$p.cor[i] <- cortest$p.val
res$cor[i] <- cortest$estimate
rm(cortest)
}
res$TPA[i] <- sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi[get(paste0(j, "_related_weak"))] < res$pvals[i], na.rm=T)
res$TPB[i] <- sum(get(paste0("pvals.", j))$p.disp.MDSeq.zi[get(paste0(j, "_related_weak"))] < res$pvals[i], na.rm=T)
res$TPboth[i] <- sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi[get(paste0(j, "_related_weak"))] < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.MDSeq.zi[get(paste0(j, "_related_weak"))] < res$pvals[i], na.rm=T)
res$TPAonly[i] <- sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi[get(paste0(j, "_related_weak"))] < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.MDSeq.zi[get(paste0(j, "_related_weak"))] >= res$pvals[i], na.rm=T)
res$TPBonly[i] <- sum(get(paste0("pvals.", j))$p.mean.MDSeq.zi[get(paste0(j, "_related_weak"))] >= res$pvals[i] &
get(paste0("pvals.", j))$p.disp.MDSeq.zi[get(paste0(j, "_related_weak"))] < res$pvals[i], na.rm=T)
}
assign(paste0(j, ".MD"), res)
write.csv(get(paste0(j, ".MD")),
here("Results/TCGA paired data results May 2020",
paste0(j, "_MDSeq_mean_v_disp_known.genes.csv")),
row.names=F)
rm(pvals, res)
pvals <- sort(unique(c(get(paste0("pvals.", j))$p.voom, get(paste0("pvals.", j))$p.disp.lnHM.log)))
res <- data.frame(
pvals = pvals,
listA = numeric(length(pvals)),
listB = numeric(length(pvals)),
overlap = numeric(length(pvals)),
p.hyper = numeric(length(pvals)),
exp.overlap = numeric(length(pvals)),
union. = numeric(length(pvals)),
p.cor = numeric(length(pvals)),
cor = numeric(length(pvals)),
TPA = numeric(length(pvals)),
TPB = numeric(length(pvals)),
TPboth = numeric(length(pvals)),
TPAonly = numeric(length(pvals)),
TPBonly = numeric(length(pvals))
)
for (i in seq_len(nrow(res))) {
res$listA[i] <- sum(get(paste0("pvals.", j))$p.voom < res$pvals[i])
res$listB[i] <- sum(get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i])
res$overlap[i] <- sum(get(paste0("pvals.", j))$p.voom < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i])
res$p.hyper[i] <- phyper(res$overlap[i],
res$listA[i],
nrow(get(paste0("pvals.", j))) - res$listA[i],
res$listB[i])
res$exp.overlap[i] <- mean(get(paste0("pvals.", j))$p.voom < res$pvals[i]) *
mean(get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]) * nrow(get(paste0("pvals.", j)))
res$union[i] <- sum(get(paste0("pvals.", j))$p.voom < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i])
if (sum(get(paste0("pvals.", j))$p.voom < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]) > 1) {
cortest <- cor.test(get(paste0("pvals.", j))$p.voom[get(paste0("pvals.", j))$p.voom < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]],
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0("pvals.", j))$p.voom < res$pvals[i] |
get(paste0("pvals.", j))$p.disp.lnHM.log < res$pvals[i]],
method="spearman", alt="less")
res$p.cor[i] <- cortest$p.val
res$cor[i] <- cortest$estimate
rm(cortest)
}
res$TPA[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPB[i] <- sum(get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPboth[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPAonly[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] < res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] >= res$pvals[i])
res$TPBonly[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] >= res$pvals[i] &
get(paste0("pvals.", j))$p.disp.lnHM.log[get(paste0(j, "_related_weak"))] < res$pvals[i])
}
assign(paste0(j, ".HMvoom"), res)
write.csv(get(paste0(j, ".HMvoom")),
here("Results/TCGA paired data results May 2020",
paste0(j, "_HM_voom_mean_v_disp_known.genes.csv")),
row.names=F)
rm(pvals, res)
pvals <- sort(unique(c(get(paste0("pvals.", j))$p.voom, 1 - get(paste0("pvals.", j))$prob.lnHMM)))
res <- data.frame(
pvals = pvals,
listA = numeric(length(pvals)),
listB = numeric(length(pvals)),
overlap = numeric(length(pvals)),
p.hyper = numeric(length(pvals)),
exp.overlap = numeric(length(pvals)),
union. = numeric(length(pvals)),
p.cor = numeric(length(pvals)),
cor = numeric(length(pvals)),
TPA = numeric(length(pvals)),
TPB = numeric(length(pvals)),
TPboth = numeric(length(pvals)),
TPAonly = numeric(length(pvals)),
TPBonly = numeric(length(pvals))
)
for (i in seq_len(nrow(res))) {
res$listA[i] <- sum(get(paste0("pvals.", j))$p.voom < res$pvals[i])
res$listB[i] <- sum(1 - get(paste0("pvals.", j))$prob.lnHMM < res$pvals[i])
res$overlap[i] <- sum(get(paste0("pvals.", j))$p.voom < res$pvals[i] &
1 - get(paste0("pvals.", j))$prob.lnHMM < res$pvals[i])
res$p.hyper[i] <- phyper(res$overlap[i],
res$listA[i],
nrow(get(paste0("pvals.", j))) - res$listA[i],
res$listB[i])
res$exp.overlap[i] <- mean(get(paste0("pvals.", j))$p.voom < res$pvals[i]) *
mean(1 - get(paste0("pvals.", j))$prob.lnHMM < res$pvals[i]) * nrow(get(paste0("pvals.", j)))
res$union[i] <- sum(get(paste0("pvals.", j))$p.voom < res$pvals[i] |
1 - get(paste0("pvals.", j))$prob.lnHMM < res$pvals[i])
if (sum(get(paste0("pvals.", j))$p.voom < res$pvals[i] |
1 - get(paste0("pvals.", j))$prob.lnHMM < res$pvals[i]) > 1) {
cortest <- cor.test(get(paste0("pvals.", j))$p.voom[get(paste0("pvals.", j))$p.voom < res$pvals[i] |
1 - get(paste0("pvals.", j))$prob.lnHMM < res$pvals[i]],
1 - get(paste0("pvals.", j))$prob.lnHMM[get(paste0("pvals.", j))$p.voom < res$pvals[i] |
1 - get(paste0("pvals.", j))$prob.lnHMM < res$pvals[i]],
method="spearman", alt="less")
res$p.cor[i] <- cortest$p.val
res$cor[i] <- cortest$estimate
rm(cortest)
}
res$TPA[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPB[i] <- sum(1 - get(paste0("pvals.", j))$prob.lnHMM[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPboth[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] < res$pvals[i] &
1 - get(paste0("pvals.", j))$prob.lnHMM[get(paste0(j, "_related_weak"))] < res$pvals[i])
res$TPAonly[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] < res$pvals[i] &
1 - get(paste0("pvals.", j))$prob.lnHMM[get(paste0(j, "_related_weak"))] >= res$pvals[i])
res$TPBonly[i] <- sum(get(paste0("pvals.", j))$p.voom[get(paste0(j, "_related_weak"))] >= res$pvals[i] &
1 - get(paste0("pvals.", j))$prob.lnHMM[get(paste0(j, "_related_weak"))] < res$pvals[i])
}
assign(paste0(j, ".HMMvoom"), res)
write.csv(get(paste0(j, ".HMMvoom")),
here("Results/TCGA paired data results May 2020",
paste0(j, "_HMM_voom_mean_v_disp_known.genes.csv")),
row.names=F)
rm(pvals, res)
}
par(mfrow=c(2,2), mar=c(4,2,2,1), mgp=c(1.5,0.5,0))
plot(lihc.HM$pvals, lihc.HM$cor, type='l', ylim=c(-1,1), col="red",
main="Correlation between ranks of genes identified by differential expression and dispersion",
xlab="p-value threshold", ylab="")
lines(lihc.MD$pvals, lihc.MD$cor, col="blue")
plot(lihc.HM$pvals, lihc.HM$p.cor, type='l', ylim=c(0,1), col="red",
main="p-value of correlation test",
xlab="p-value threshold for differential expression or dispersion", ylab="")
lines(lihc.MD$pvals, lihc.MD$p.cor, col="blue")
plot(lihc.HM$pvals, lihc.HM$overlap / lihc.HM$union, type='l', ylim=c(0,1), col="red",
main="Union / Intersection",
xlab="p-value threshold", ylab="")
lines(lihc.MD$pvals, lihc.MD$overlap / lihc.MD$union, col='blue',
xlab="p-value threshold", ylab="")
plot(lihc.HM$pvals, lihc.HM$p.hyper, type='l', ylim=c(0,1), col="red",
main="p-value of test of overlap",
xlab="p-value threshold", ylab="")
lines(lihc.MD$pvals, lihc.MD$p.hyper, col='blue')
# genes identified by diff disp/dist missed by DE
par(mfrow=c(2,2), mar=c(4,2,2,1), mgp=c(1.5,0.5,0))
plot(lihc.HM$pvals, lihc.HM$TPA, type='l', col='red')
lines(lihc.HM$pvals, lihc.HM$TPB, col='blue')
lines(lihc.HM$pvals, lihc.HM$TPboth, col='grey')
lines(lihc.HM$pvals, lihc.HM$TPAonly, col='red', lty=2)
lines(lihc.HM$pvals, lihc.HM$TPBonly, col='blue', lty=2)
plot(lihc.MD$pvals, lihc.MD$TPA, type='l', col='red')
lines(lihc.MD$pvals, lihc.MD$TPB, col='blue')
lines(lihc.MD$pvals, lihc.MD$TPboth, col='grey')
lines(lihc.MD$pvals, lihc.MD$TPAonly, col='red', lty=2)
lines(lihc.MD$pvals, lihc.MD$TPBonly, col='blue', lty=2)
plot(lihc.HMvoom$pvals, lihc.HMvoom$TPA, type='l', col='red',
main="Genes identified by differential expression (red) and differential dispersion (blue)",
ylab="", xlab="p-value threshold")
lines(lihc.HMvoom$pvals, lihc.HMvoom$TPB, col='blue')
lines(lihc.HMvoom$pvals, lihc.HMvoom$TPboth, col='grey')
lines(lihc.HMvoom$pvals, lihc.HMvoom$TPAonly, col='red', lty=2)
lines(lihc.HMvoom$pvals, lihc.HMvoom$TPBonly, col='blue', lty=2)
plot(lihc.HMMvoom$pvals, lihc.HMMvoom$TPA, type='l', col='red',
main="Genes identified by differential expression (red) and differential distribution (blue)",
ylab="", xlab="p-value threshold")
lines(lihc.HMMvoom$pvals, lihc.HMMvoom$TPB, col='blue')
lines(lihc.HMMvoom$pvals, lihc.HMMvoom$TPboth, col='grey')
lines(lihc.HMMvoom$pvals, lihc.HMMvoom$TPAonly, col='red', lty=2)
lines(lihc.HMMvoom$pvals, lihc.HMMvoom$TPBonly, col='blue', lty=2)