GTEx eQTL pipeline

This repository analyzes eQTLs for brain and nerve tissues per sex using the GTEx eQTL pipeline docker image.

Subset samples and tissues desired

00-setup.sh should be run first to setup folders, symbolic links and cleaner covariate files, PLINK files, etc.

phenotypes_eda.ipynb shows the reasoning on how to list out the tissue sample ID's per brain and tibial nerve tissues and per sex. Due to the sensitive nature of the data, the outputs have been cleared.

01-run_eqtl_pipeline.sh goes through the GTEx eQTL pipeline as closely as possible for the sample subsets that were generated in phenotypes_eda.ipynb step

01-submit_eqtl_pipeline is to submit each of the sample subsets generated as a job on the hpc

eQTL analyses were adjusted for:

• Top 5 genotyping principal components.
• A set of covariates identified using the Probabilistic Estimation of Expression Residuals (PEER) method (Stegle et al., PLoS Comp. Biol., 2010 ), calculated for the normalized expression matrices (described below). For eQTL analyses, the number of PEER factors was determined as function of sample size (N): 15 factors for N<150, 30 factors for 150≤ N<250, 45 factors for 250≤ N<350, and 60 factors for N≥350, as a result of optimizing for the number of eGenes discovered. For sQTL analyses, 15 PEER factors were computed for each tissue.
• Sequencing platform (Illumina HiSeq 2000 or HiSeq X).
• Sequencing protocol (PCR-based or PCR-free).
• Sex. Although this was dropped by combined_covariates.py due to collinearity (since each subset is one sex).
• Age (note: this is not adjusted for in the public analyses).