Normalizing Metagenomic Hi-C Data and Detecting Spurious Contacts Using Zero-Inflated Negative Binomial Regression.

ABSTRACT: High-throughput chromosome conformation capture (Hi-C) has recently been applied to natural microbial communities and revealed great potential to study multiple genomes simultaneously. Several extraneous factors may influence chromosomal contacts rendering the normalization of Hi-C contact maps essential for downstream analyses. However, the current paucity of metagenomic Hi-C normalization methods and the ignorance for spurious interspecies contacts weaken the interpretability of the data. Here, we report on two types of biases in metagenomic Hi-C experiments: explicit biases and implicit biases, and introduce HiCzin, a parametric model to correct both types of biases and remove spurious interspecies contacts. We demonstrate that the normalized metagenomic Hi-C contact maps by HiCzin resu

SUBMITTER: Du Y 

PROVIDER: S-EPMC8892984 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature