StateHub-StatePaintR: rapid and reproducible chromatin state evaluation for custom genome annotation

Simon G Coetzee,Benjamin P Berman,Zachary Ramjan,Huy Q Dinh,Dennis J Hazelett

doi:10.12688/f1000research.13535.2

Simon G Coetzee, Benjamin P Berman + Show 3 more

Open Access

https://doi.org/10.12688/f1000research.13535.2

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Journal: F1000Research	Publication Date: May 7, 2020
Citations: 4	License type: CC BY 4.0

Affiliation: Cedars-Sinai Medical Center, Van Andel Institute

Abstract

Genome annotation is critical to understand the function of disease variants, especially for clinical applications. To meet this need there are segmentations available from public consortia reflecting varying unsupervised approaches to functional annotation based on epigenetics data, but there remains a need for transparent, reproducible, and easily interpreted genomic maps of the functional biology of chromatin. We introduce a new methodological framework for defining a combinatorial epigenomic model of chromatin state on a web database, StateHub. In addition, we created an annotation tool for bioconductor, StatePaintR, which accesses these models and uses them to rapidly (on the order of seconds) produce chromatin state segmentations in standard genome browser formats. Annotations are fully documented with change history and versioning, authorship information, and original source files. StatePaintR calculates ranks for each state from next-gen sequencing peak statistics, facilitating variant prioritization, enrichment testing, and other types of quantitative analysis. StateHub hosts annotation tracks for major public consortia as a resource, and allows users to submit their own alternative models.

Highlights

Genome annotation is critical to understand the function of disease variants, especially for clinical applications
The decision matrix encodes the relationship between these functional categories and specific chromatin states, where the values of any particular cell of this matrix must take any of 4 different values (Table 1) indicating the nature of the relationship
A framework for rule-based annotation In order to assign chromatin states, it is necessary to account for the complex interplay of input from genomic annotations and cell-type-specific experimental data sources that define and demarcate functional regions of the genome[1]

Summary

Introduction

Genome annotation is critical to understand the function of disease variants, especially for clinical applications. To meet this need there are segmentations available from public consortia reflecting varying unsupervised approaches to functional annotation based on epigenetics data, but there remains a need for transparent, reproducible, and interpreted genomic maps of the functional biology of chromatin. We introduce a new methodological framework for defining a combinatorial epigenomic model of chromatin state on a web database, StateHub. In addition, we created an annotation tool for bioconductor, StatePaintR, which accesses these models and uses them to rapidly (on the order of seconds) produce chromatin state segmentations in standard genome browser formats. StateHub hosts annotation tracks for major public consortia as a resource, and allows users to submit their own alternative models

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