TRECASE_MLE: eQTL mapping based on total read count and allele-specific expression in RNA-Seq data with maximum-likelihood estimation (C/C++).

TitleTRECASE_MLE: eQTL mapping based on total read count and allele-specific expression in RNA-Seq data with maximum-likelihood estimation (C/C++).
Publication TypeSoftware
Year of Publication2015
AuthorsSong, Guochen
Abstract

TRECASE_MLE is a command-line program written in C/C++ for eQTL mapping with RNA-seq data. TRECASE_MLE implemented the following steps in the five-step pipeline: (step 1) testing every local SNP for association with the expression of a gene and reporting the SNP with the minimum p-value (referred to as the minimum-p SNP) for each gene; (step 2) assessing the significance of every minimum-p SNP by a permutation process; (step 4) conducting the cis-trans test at every minimum-p SNP; and (step 5) estimating the effect size at every minimum-p SNP. All of these steps are performed for the TReC and TReCASE models in parallel. Note that Step 3 in the five-step pipeline that detects eQTLs among genome-wide minimum-p SNPs by FDR control can be performed using the R utility program “detect_eQTLs_byFDRcontrol.R” (provided in the zip file) based on the output of TRECASE_MLE; this R program generates the final list of detected eQTLs with determined cis or trans mechanisms and estimated effect sizes.

Original PublicationTRECASE_MLE: eQTL mapping based on total read count and allele-specific expression in RNA-Seq data with maximum-likelihood estimation (C/C++).
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