Genomics, Proteomics & Bioinformatics (Jun 2023)

Computational Assessment of the Expression-modulating Potential for Non-coding Variants

  • Fang-Yuan Shi,
  • Yu Wang,
  • Dong Huang,
  • Yu Liang,
  • Nan Liang,
  • Xiao-Wei Chen,
  • Ge Gao

Journal volume & issue
Vol. 21, no. 3
pp. 662 – 673

Abstract

Read online

Large-scale genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression. However, pinpointing causal variants effectively and efficiently remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional non-coding expression-modulating variants. Multiple evaluations demonstrated CARMEN’s superior performance over state-of-the-art tools. Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms (SNPs). CARMEN scales well with the massive datasets, and is available online as a web server at http://carmen.gao-lab.org.

Keywords