Measuring the reproducibility and quality of Hi-C data.

ABSTRACT:

Background

Hi-C is currently the most widely used assay to investigate the 3D organization of the genome and to study its role in gene regulation, DNA replication, and disease. However, Hi-C experiments are costly to perform and involve multiple complex experimental steps; thus, accurate methods for measuring the quality and reproducibility of Hi-C data are essential to determine whether the output should be used further in a study.

Results

Using real and simulated data, we profile the performance of several recently proposed methods for assessing reproducibility of population Hi-C data, including HiCRep, GenomeDISCO, HiC-Spector, and QuASAR-Rep. By explicitly controlling noise and sparsity through simulations, we demonstrate the deficiencies of performing simple correlation

SUBMITTER: Yardımcı GG 

PROVIDER: S-EPMC6423771 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature