ChromGene: gene-based modeling of epigenomic data

Artur Jaroszewicz; Jason Ernst

doi:10.1186/s13059-023-03041-5

ChromGene: gene-based modeling of epigenomic data

Genome Biol. 2023 Sep 7;24(1):203. doi: 10.1186/s13059-023-03041-5.

Authors

Artur Jaroszewicz^{1

2}, Jason Ernst^{3

4

5

6

7

8

9}

Affiliations

¹ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
² Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
³ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA. jason.ernst@ucla.edu.
⁴ Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA. jason.ernst@ucla.edu.
⁵ Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA, 90095, USA. jason.ernst@ucla.edu.
⁶ Computer Science Department, University of California, Los Angeles, Los Angeles, CA, 90095, USA. jason.ernst@ucla.edu.
⁷ Computational Medicine Department, University of California, Los Angeles, Los Angeles, CA, 90095, USA. jason.ernst@ucla.edu.
⁸ Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA. jason.ernst@ucla.edu.
⁹ Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA. jason.ernst@ucla.edu.

Abstract

Various computational approaches have been developed to annotate epigenomes on a per-position basis by modeling combinatorial and spatial patterns within epigenomic data. However, such annotations are less suitable for gene-based analyses. We present ChromGene, a method based on a mixture of learned hidden Markov models, to annotate genes based on multiple epigenomic maps across the gene body and flanks. We provide ChromGene assignments for over 100 cell and tissue types. We characterize the mixture components in terms of gene expression, constraint, and other gene annotations. The ChromGene method and annotations will provide a useful resource for gene-based epigenomic analyses.

Keywords: Chromatin; Epigenomics; Hidden Markov models; Histone modifications; Machine learning.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Epigenome*
Epigenomics*
Histocompatibility Testing
Learning
Molecular Sequence Annotation

Abstract

Publication types

MeSH terms

Grants and funding