Open AccessCapturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data
Author(s) -
Hyeon Jin Kim,
Galip Gürkan Yardımcı,
Giancarlo Bonora,
Vijay Ramani,
Jie Liu,
Ruolan Qiu,
Choli Lee,
Jennifer Hesson,
Carol B. Ware,
Jay Shendure,
Zhijun Duan
Publication year - 2020
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1008173
Subject(s) - chromatin , cell type , computational biology , compartment (ship) , cell , single cell analysis , computer science , biology , genetics , dna , oceanography , geology
Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of “chromatin topics.” We further show enrichment of particular compartment structures associated with locus pairs in these topics.