Last updated: 2020-03-17
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Knit directory: m6AQTL_reproducibleDocument/
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sumStat<- read.table("~/m6AQTL/other_phenotypes/summary_betas_ste_100kb.txt",sep = " ", header = T)
Tx4SU_30min <- Tx4SU_60min <- sumStat[,c("chr","pos","geneID")]
Tx4SU_30min$beta <- as.numeric(unlist( lapply( strsplit(as.character(sumStat$X4su_30),":"),function(x) x[2] ) ))
Tx4SU_30min$std.err <- as.numeric( unlist( lapply( strsplit(as.character(sumStat$X4su_30),":"),function(x) x[3] ) ) )
Tx4SU_30min$pvalue <- as.numeric( unlist( lapply( strsplit(as.character(sumStat$X4su_30),":"),function(x) x[1] ) ) )
Tx4SU_60min$beta <- as.numeric(unlist( lapply( strsplit(as.character(sumStat$X4su_60),":"),function(x) x[2] ) ) )
Tx4SU_60min$std.err <- as.numeric( unlist( lapply( strsplit(as.character(sumStat$X4su_60),":"),function(x) x[3] ) ) )
Tx4SU_60min$pvalue <- as.numeric( unlist( lapply( strsplit(as.character(sumStat$X4su_60),":"),function(x) x[1] ) ) )
Tx4SU_30min$pQTL_beta <- Tx4SU_60min$pQTL_beta <- as.numeric(unlist( lapply( strsplit(as.character(sumStat$prot),":"),function(x) x[2] ) ))
Tx4SU_30min$eQTL_beta <- as.numeric(unlist( lapply( strsplit(as.character(sumStat$RNAseq),":"),function(x) x[2] ) ))
m6AQTL <- readRDS("~/m6AQTL/m6A_QTL_results/linear_model/m6AQTL.m6APeak_logOR_GC.IP.adjusted_qqnorm.15PCs.fastQTL.nominals.rds")
GTF <- rtracklayer::import("~/Database/genome/GRCh37/GRCh37.gencode.v27.gtf",format = "gtf")
GTFmap <- data.frame("ENSEMBL" = GTF$gene_id,"Symbol" = GTF$gene_name)
GTFmap <- GTFmap[!duplicated(GTFmap$ENSEMBL),]
GTFmap$ENSEMBL <- unlist(lapply(strsplit(as.character(GTFmap$ENSEMBL), "[.]"),function(x) x[1]))
Tx4SU_30min$geneSymbol <- GTFmap$Symbol[match(Tx4SU_30min$geneID,GTFmap$ENSEMBL)]
Tx4SU_60min$geneSymbol <- GTFmap$Symbol[match(Tx4SU_60min$geneID,GTFmap$ENSEMBL)]
Tx4SU_30min$qvalue <- qvalue::qvalue(Tx4SU_30min$pvalue)$qvalue
Tx4SU_60min$qvalue <- qvalue::qvalue(Tx4SU_60min$pvalue)$qvalue
m6AQTL$peakGene <- unlist(lapply(strsplit(as.character(m6AQTL$PEAK), split = "_"),function(x) x[2]))
m6AQTL$SnpGenePair <- paste(m6AQTL$SNP, m6AQTL$peakGene, sep = ".")
m6AQTL <- m6AQTL[order(m6AQTL$pvalue),]
eQTL <- readRDS("~/m6AQTL/other_phenotypes/eQTL/eQTL_summaryStats.RDS")sig.Tx4SU_30min <- Tx4SU_30min[Tx4SU_30min$pvalue<1e-4,]
sig.Tx4SU_60min <- Tx4SU_30min[Tx4SU_60min$pvalue<1e-4,]
sig.Tx4SU_30min <- sig.Tx4SU_30min[order(sig.Tx4SU_30min$pvalue),]
sig.Tx4SU_60min <- sig.Tx4SU_60min[order(sig.Tx4SU_60min$pvalue),]
sig.Tx4SU_30min_lead <- sig.Tx4SU_30min[!duplicated(sig.Tx4SU_30min$geneID),]
sig.Tx4SU_60min_lead <- sig.Tx4SU_60min[!duplicated(sig.Tx4SU_60min$geneID),]
sig.Tx4SU_30min_lead$m6A <- m6AQTL$beta[match(paste0(sig.Tx4SU_30min_lead$chr,":",sig.Tx4SU_30min_lead$pos,".",sig.Tx4SU_30min_lead$geneSymbol),m6AQTL$SnpGenePair)]
sig.Tx4SU_60min_lead$m6A <- m6AQTL$beta[match(paste0(sig.Tx4SU_60min_lead$chr,":",sig.Tx4SU_60min_lead$pos,".",sig.Tx4SU_60min_lead$geneSymbol),m6AQTL$SnpGenePair)]
save(sig.Tx4SU_30min_lead,sig.Tx4SU_60min_lead, file = "~/m6AQTL/m6AQTL_analysis/data/TxQTL_m6AQTL_linearModel_effectSize_correlation.RData")library(ggplot2)
library(ggpmisc)
load(file = "~/m6AQTL/m6AQTL_analysis/data/TxQTL_m6AQTL_linearModel_effectSize_correlation.RData")
ggplot(sig.Tx4SU_30min_lead,aes(x = beta, y = m6A)) +geom_point()+ggtitle("")+ylab("m6A-QTL effect size") + xlab("Tx-QTL (30min 4SU labeling) effect size") +stat_smooth(method = 'lm')+ geom_hline(aes(yintercept = 0), colour="#990000", linetype="dashed") +theme_classic() + theme(axis.line = element_line(colour = "black",size = I(0.75)),axis.title = element_text(family = "arial", face = "bold",size = 15),axis.text = element_text(family = "arial", face = "bold", size = 12), plot.title = element_text(family = "arial", face = "bold", size = 14, hjust = 0.5), legend.position = "none" )+stat_poly_eq(aes(label = paste(..rr.label..)), label.x.npc = "left", label.y.npc = 0.95, formula = y~x, parse = TRUE, size = 5)ggplot(sig.Tx4SU_60min_lead,aes(x = beta, y = m6A)) +geom_point()+ggtitle("")+ylab("m6A-QTL effect size") + xlab("Transcription-QTL (60min 4SU labeling) effect size") +stat_smooth(method = 'lm')+ geom_hline(aes(yintercept = 0), colour="#990000", linetype="dashed") +theme_classic() + theme(axis.line = element_line(colour = "black",size = I(0.75)),axis.title = element_text(family = "arial", face = "bold",size = 15),axis.text = element_text(family = "arial", face = "bold", size = 12), plot.title = element_text(family = "arial", face = "bold", size = 14, hjust = 0.5), legend.position = "none" )+stat_poly_eq(aes(label = paste(..rr.label..)), label.x.npc = "left", label.y.npc = 0.95, formula = y~x, parse = TRUE, size = 5)load("~/m6AQTL/m6AQTL_analysis/data/TxQTL_epQTL_linearModel_effectSize_correlation.RData")
Tx4SU_30min_p4 <- Tx4SU_30min_p4[!duplicated(Tx4SU_30min_p4$geneID)& Tx4SU_30min_p4$pQTL_beta<10,]
Tx4SU_60min_p4 <- Tx4SU_60min_p4[!duplicated(Tx4SU_60min_p4$geneID) ,]
ggplot(Tx4SU_30min_p4,aes(x = beta, y = eQTL_beta))+geom_point( size = 3)+ylab("eQTL effect sizes")+xlab("Txn-QTL effect size (4SU 30 min)")+stat_smooth( method = 'lm')+theme_bw() +
geom_hline(yintercept = 0, lty= 2, colour="#990000")+
theme(panel.grid = element_blank(),axis.line = element_line(colour = "black",size = I(1.6)),axis.ticks = element_line(colour = "black",size = I(1.6)), panel.border =element_rect(colour = "black",size = I(1)) ,axis.title = element_text(family = "arial", face = "bold", size = 15),axis.text = element_text(family = "arial", face = "bold", size = 30,colour = "black"), plot.title = element_text(family = "arial", face = "bold", size = 14, hjust = 0.5), legend.position = "none", strip.text = element_text(face = "bold", size = 14), panel.grid.minor = element_blank() )+stat_poly_eq(aes(label = paste(..rr.label..)), label.x.npc = 0.14, label.y.npc = 0.92, formula = y~x, parse = TRUE, size = 14,coef.digits = 2)
ggplot(Tx4SU_60min_p4,aes(x = beta, y = eQTL_beta))+geom_point( size = 3)+ylab("eQTL effect sizes")+xlab("Txn-QTL effect size (4SU 60 min)")+stat_smooth( method = 'lm')+theme_bw() +
geom_hline(yintercept = 0, lty= 2, colour="#990000")+
theme(panel.grid = element_blank(),axis.line = element_line(colour = "black",size = I(1.6)),axis.ticks = element_line(colour = "black",size = I(1.6)), panel.border =element_rect(colour = "black",size = I(1)) ,axis.title = element_text(family = "arial", face = "bold", size = 15),axis.text = element_text(family = "arial", face = "bold", size = 30,colour = "black"), plot.title = element_text(family = "arial", face = "bold", size = 14, hjust = 0.5), legend.position = "none", strip.text = element_text(face = "bold", size = 14), panel.grid.minor = element_blank() )+stat_poly_eq(aes(label = paste(..rr.label..)), label.x.npc = 0.14, label.y.npc = 0.92, formula = y~x, parse = TRUE, size = 14,coef.digits = 2)
ggplot(Tx4SU_30min_p4,aes(x = beta, y = pQTL_beta))+geom_point( size = 3)+ylab("Protein-QTL effect sizes")+xlab("Txn-QTL effect size (4SU 30 min)")+stat_smooth( method = 'lm')+theme_bw() +
geom_hline(yintercept = 0, lty= 2, colour="#990000")+
theme(panel.grid = element_blank(),axis.line = element_line(colour = "black",size = I(1.6)),axis.ticks = element_line(colour = "black",size = I(1.6)), panel.border =element_rect(colour = "black",size = I(1)) ,axis.title = element_text(family = "arial", face = "bold", size = 15),axis.text = element_text(family = "arial", face = "bold", size = 30,colour = "black"), plot.title = element_text(family = "arial", face = "bold", size = 14, hjust = 0.5), legend.position = "none", strip.text = element_text(face = "bold", size = 14), panel.grid.minor = element_blank() )+stat_poly_eq(aes(label = paste(..rr.label..)), label.x.npc = 0.14, label.y.npc = 0.92, formula = y~x, parse = TRUE, size = 14,coef.digits = 2)
ggplot(Tx4SU_60min_p4,aes(x = beta, y = pQTL_beta))+geom_point( size = 3)+ylab("Protein-QTL effect sizes")+xlab("Txn-QTL effect size (4SU 60 min)")+stat_smooth( method = 'lm')+theme_bw() +
geom_hline(yintercept = 0, lty= 2, colour="#990000")+
theme(panel.grid = element_blank(),axis.line = element_line(colour = "black",size = I(1.6)),axis.ticks = element_line(colour = "black",size = I(1.6)), panel.border =element_rect(colour = "black",size = I(1)) ,axis.title = element_text(family = "arial", face = "bold", size = 15),axis.text = element_text(family = "arial", face = "bold", size = 30,colour = "black"), plot.title = element_text(family = "arial", face = "bold", size = 14, hjust = 0.5), legend.position = "none", strip.text = element_text(face = "bold", size = 14), panel.grid.minor = element_blank() )+stat_poly_eq(aes(label = paste(..rr.label..)), label.x.npc = 0.14, label.y.npc = 0.92, formula = y~x, parse = TRUE, size = 14,coef.digits = 2)
sessionInfo()R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 17.10
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] workflowr_1.3.0 Rcpp_1.0.1 digest_0.6.18 rprojroot_1.3-2
[5] backports_1.1.4 git2r_0.25.2 magrittr_1.5 evaluate_0.13
[9] stringi_1.4.3 fs_1.3.0 rmarkdown_1.12 tools_3.5.3
[13] stringr_1.4.0 glue_1.3.1 xfun_0.6 yaml_2.2.0
[17] compiler_3.5.3 htmltools_0.3.6 knitr_1.22