RT Journal Article
SR Electronic
T1 QuASAR: Quantitative Allele Specific Analysis of Reads
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 007492
DO 10.1101/007492
A1 Chris T. Harvey
A1 Gregory A. Moyerbrailean
A1 Gordon O. Davis
A1 Xiaoquan Wen
A1 Francesca Luca
A1 Roger Pique-Regi
YR 2014
UL http://biorxiv.org/content/early/2014/12/05/007492.abstract
AB Motivation Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls.Results We present QuASAR, Quantitative Allele Specific Analysis of Reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available.Availability http://github.com/piquelab/QuASARContact fluca{at}wayne.edu; rpique{at}wayne.edu