PICALO: principal interaction component analysis for the identification of discrete technical, cell-type, and environmental factors that mediate eQTLs

PICALO: principal interaction component analysis for the identification of discrete technical, cell-type, and environmental factors that mediate eQTLs

Abstract Expression quantitative trait loci (eQTL) offer insights into the regulatory mechanisms of trait-associated variants, but their effects often rely on contexts that are unknown or unmeasured. We introduce PICALO, a method for hidden variable inference of eQTL contexts. PICALO identifies and...

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Bibliographic Details
Main Authors: Martijn Vochteloo, Patrick Deelen, Britt Vink, BIOS Consortium, Ellen A. Tsai, Heiko Runz, Sergio Andreu-Sánchez, Jingyuan Fu, Alexandra Zhernakova, Harm-Jan Westra, Lude Franke
Format: Article
Language:English
Published: BMC 2024-01-01
Series:Genome Biology
Subjects:
eQTLs
Hidden variable inference
Context
Cell type
Interaction eQTLs
Online Access:https://doi.org/10.1186/s13059-023-03151-0

Internet

https://doi.org/10.1186/s13059-023-03151-0

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