Chrom-Lasso: a lasso regression-based model to detect functional interactions using Hi-C data.

ABSTRACT: Hi-C is a genome-wide assay based on Chromosome Conformation Capture and high-throughput sequencing to decipher 3D chromatin organization in the nucleus. However, computational methods to detect functional interactions utilizing Hi-C data face challenges including the correction for various sources of biases and the identification of functional interactions with low counts of interacting fragments. We present Chrom-Lasso, a lasso linear regression model that removes complex biases assumption-free and identifies functional interacting loci with increased power by combining information of local reads distribution surrounding the area of interest. We showed that interacting regions identified by Chrom-Lasso are more enriched for 5C validated interactions and functional GWAS hits than that of

SUBMITTER: Lu J 

PROVIDER: S-EPMC8574949 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature