Author: Charleen D. Adams

Abbreviations and definitions

Forest plots for all RP eQTLs (color coded)

My goal with these plots is to show the big picture of which RPs increase or decrease expression across all tissues for which an eQTL had been identified.

Thoughts: I removed the tissue labels since to make them legible makes the individual plots too big.

We can zoom in individual genes for a grandular look in separate plots. It might make sense to do this for some of the genes for which there are both increased and decreased expression eQTLs.

## Set up
## Load the data: merged_EAF contains the eGene signficant eQTLs (Q-value<0.05 & nominal P<5x10-6)
load("C:/Users/charl/Dropbox/Harvard/ribosomal_proteins/Main_Tables_Paper/v8/V8_masterRP_lists_mergedEAF_matrices.Rdata")

## Select the RPL9 data
RPL9 <- grepl.sub(data = merged_EAF, pattern = "RPL9", Var = "gene_name")

Zooming in on RPL9

All the eQTLs for RPL9 decreased expression.

Plan

There are five eQTLs for RPL9:

I had keyed into RPL9 due to the preliminary phenotypic analysis for breast cancer, for which some of these SNPs increased risk. I’ll look to see if they increase risk for lung and prostate cancers later.

Forest plot for RPS26

Big picture: Displaying both the effect sizes and the -log10(P)-values

To make the effect size axis center at zero, I created a dummy row and later erased the observation it generated.

Extra plots

Breast, lung, prostate, and ovary

Effect sizes

Github

Copy this link into your browser if Github doesn’t link: https://github.com/charleendadams/ribosomal_protein_eQTLs