# Genome-wide identification and analysis of recurring patterns of epigenetic variation across individuals

## TL;DR

This paper introduces a new method to identify recurring epigenetic patterns across the genome and shows how these patterns relate to gene expression and complex disorders like autism.

## Contribution

A stacked chromatin state model is introduced to systematically identify and analyze global epigenetic patterns across individuals.

## Key findings

- Global epigenetic patterns correlate with multiple histone modifications and gene expression.
- The identified patterns can be used to predict trans-regulators and study complex disorders.
- The framework is generalizable and applicable to other biological systems.

## Abstract

Epigenetic mapping studies across individuals have identified many positions of epigenetic variation across the human genome. However the relationships between these positions, and in particular global patterns that recur in many regions of the genome, remains understudied. In this study, we use a stacked chromatin state model to systematically learn global patterns of epigenetic variation across individuals and annotate the human genome based on them. We apply this framework to histone modification data across individuals in lymphoblastoid cell lines and across autism spectrum disorder cases and controls in prefrontal cortex tissue. We find that global patterns are correlated across multiple histone modifications and with gene expression. We use the global patterns as a framework to predict trans-regulators and study a complex disorder. The frameworks for identifying and analyzing global patterns of epigenetic variation are general and we expect will be useful in other systems.

Recurring genome-wide patterns of epigenetic mark variation across individuals learned through computational modeling relate to external measures of molecular variation and can be used to study gene regulation and complex phenotypes.