Yang et al. (2013) introduced LORS, a method that jointly models the expression of genes, SNPs, and hidden factors for eQTL mapping. LORS solves a convex optimization problem and has guaranteed convergence. However, it can be computationally expensive for large datasets. In this paper we introduce Fast-LORS which uses the proximal gradient method to solve the LORS problem with significantly reduced computational burden. We apply Fast-LORS and LORS to data from the third phase of the International HapMap Project and obtain comparable results. Nevertheless, Fast-LORS shows substantial computational improvement compared to LORS.
Cite
@article{arxiv.1805.05170,
title = {FastLORS: Joint Modeling for eQTL Mapping in R},
author = {Jacob Rhyne and Eric Chi and Jung-Ying Tzeng and X. Jessie Jeng},
journal= {arXiv preprint arXiv:1805.05170},
year = {2018}
}
Comments
All functions are available in the FastLORS R package, available at https://github.com/jdrhyne2/FastLORS