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eQTL analysis on TCGA RNAseq data and SNP6 data

Hi,

I'm trying to carry out eQTL analysis using genotype calls from SNP6 array(calls made using CRLMM) and expression from RNAseq from TCGA. I carried out routine QC and population stratification on the genotype data. I also filter gene expression data to remove genes that are with 90th percentile expression < 30 and transform the expression data to a normal distribution while retaining rank as advised in the tutorial for MatrixEQTL. I have a huge inflation in p-values (very very low p-values in the order of e-300) when I carry out eQTL analysis. I have tried adding upto 150 covariates using PEER, however it does little impact on the p-values I obtain. I also tried correcting the expression data for copy number effects by using residuals obtained after regression expression against CN as descried in http://www.cell.com/cell/fulltext/S0092-8674(12)01556-5.

I will be grateful for any advice on how I can correct my expression or genotype data to improve eQTL calling.

Thanking You, Vakul

eqtl analysis matrixeqtl tcga rnaseq

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