HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient.

ABSTRACT: Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desir

SUBMITTER: Yang T 

PROVIDER: S-EPMC5668950 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature