Effective normalization for copy number variation in Hi-C data.

ABSTRACT:

Background

Normalization is essential to ensure accurate analysis and proper interpretation of sequencing data, and chromosome conformation capture data such as Hi-C have particular challenges. Although several methods have been proposed, the most widely used type of normalization of Hi-C data usually casts estimation of unwanted effects as a matrix balancing problem, relying on the assumption that all genomic regions interact equally with each other.

Results

In order to explore the effect of copy-number variations on Hi-C data normalization, we first propose a simulation model that predict the effects of large copy-number changes on a diploid Hi-C contact map. We then show that the standard approaches relying on equal visibility fail to correct for unwanted effects in the p

SUBMITTER: Servant N 

PROVIDER: S-EPMC6127909 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature