TY - JOUR
T1 - EQTLHap
T2 - A tool for comprehensive eQTL analysis considering haplotypic and genotypic effects
AU - Al Bkhetan, Ziad
AU - Chana, Gursharan
AU - Soon Ong, Cheng
AU - Goudey, Benjamin
AU - Ramamohanarao, Kotagiri
N1 - Publisher Copyright:
© 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected].
PY - 2021/9/1
Y1 - 2021/9/1
N2 - Motivation: The high accuracy of recent haplotype phasing tools is enabling the integration of haplotype (or phase) information more widely in genetic investigations. One such possibility is phase-aware expression quantitative trait loci (eQTL) analysis, where haplotype-based analysis has the potential to detect associations that may otherwise be missed by standard SNP-based approaches. Results: We present eQTLHap, a novel method to investigate associations between gene expression and genetic variants, considering their haplotypic and genotypic effect. Using multiple simulations based on real data, we demonstrate that phase-aware eQTL analysis significantly outperforms typical SNP-based methods when the causal genetic architecture involves multiple SNPs. We show that phase-aware eQTL analysis is robust to phasing errors, showing only a minor impact ($<4\%$) on sensitivity. Applying eQTLHap to real GEUVADIS and GTEx datasets detects numerous novel eQTLs undetected by a single-SNP approach, with 22 eQTLs replicating across studies or tissue types, highlighting the utility of phase-aware eQTL analysis. Contact: [email protected]
AB - Motivation: The high accuracy of recent haplotype phasing tools is enabling the integration of haplotype (or phase) information more widely in genetic investigations. One such possibility is phase-aware expression quantitative trait loci (eQTL) analysis, where haplotype-based analysis has the potential to detect associations that may otherwise be missed by standard SNP-based approaches. Results: We present eQTLHap, a novel method to investigate associations between gene expression and genetic variants, considering their haplotypic and genotypic effect. Using multiple simulations based on real data, we demonstrate that phase-aware eQTL analysis significantly outperforms typical SNP-based methods when the causal genetic architecture involves multiple SNPs. We show that phase-aware eQTL analysis is robust to phasing errors, showing only a minor impact ($<4\%$) on sensitivity. Applying eQTLHap to real GEUVADIS and GTEx datasets detects numerous novel eQTLs undetected by a single-SNP approach, with 22 eQTLs replicating across studies or tissue types, highlighting the utility of phase-aware eQTL analysis. Contact: [email protected]
UR - http://www.scopus.com/inward/record.url?scp=85116172754&partnerID=8YFLogxK
U2 - 10.1093/bib/bbab093
DO - 10.1093/bib/bbab093
M3 - Article
SN - 1467-5463
VL - 22
JO - Briefings in Bioinformatics
JF - Briefings in Bioinformatics
IS - 5
M1 - bbab093
ER -