# Integrated analysis of genetic variation and epigenomic data

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $520,416

## Abstract

Project Summary:
The large majority of genetic variations (GVs) occur in non-coding regions particularly in intergenic regions.
Understanding the functions of the GVs and revealing their regulatory impact on gene expression remain a
great challenge because it is not trivial to link GVs to their target genes and consider collaborative effect of
individual GVs. The availability of large amount of the ENCODE and Roadmap Epigenomics Project data
provides an unprecedented opportunity to tackle these challenges. We will develop new computational
methods to predict long-range promoter-enhancer interactions from epigenomic data. These predicted
promoter-enhancer interactions will be integrated with the other ENCODE and Roadmap Epigenomics Project
data including histone modification, ChIP-seq of DNA binding proteins, RNA-seq and open chromatin data to
construct genetic networks that represent cell-type specific regulatory interactions. These networks will be
used to annotate the GVs identified in patient samples to reveal disease-related GVs. Once completed, the
proposed study will provide a suite of new computational methods for integrative analysis of the
ENCODE/Epigenome Roadmap data and establish a resource of the digested ENCODE/Roadmap
Epigenomics Project data. The proposed computational framework is general and can be easily applied to
other public data.

## Key facts

- **NIH application ID:** 9898420
- **Project number:** 5R01HG009626-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Wei Wang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $520,416
- **Award type:** 5
- **Project period:** 2017-06-03 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9898420

## Citation

> US National Institutes of Health, RePORTER application 9898420, Integrated analysis of genetic variation and epigenomic data (5R01HG009626-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9898420. Licensed CC0.

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