# Realtime visualization and analytics of epigenomic data using a serverless architecture

> **NIH NIH R43** · BASEPAIR, INC. · 2020 · $348,442

## Abstract

PROJECT SUMMARY
 Epigenetics describes the study of phenotypic outcomes due to alterations in gene expression without
changes to the coding DNA. The field has exploded in the past decade with the recognition that epigenetic factors
(e.g. histone post-translational modifications, chromatin-associated proteins, DNA methylation) regulate gene
expression and diverse downstream cellular processes, including the development of human disease. Next
Generation Sequencing (NGS) studies of these epigenetic changes have enabled a more fundamental
understanding of how chromatin structure impacts human health and revealed new targets for drug development.
The importance of this field has driven remarkable advances in epigenomic profiling; however, innovations in
methods to intelligibly interpret, compare, and visualize this mass of epigenetic data have lagged behind. The
current framework for these tertiary analyses is slow, too technical for most users, and unable to process the
increasingly complex queries that are required for epigenetic discovery.
 Basepair® is an industry leader in streamlined NGS analysis pipelines. Here, we will leverage this
expertise with the development of EpiBeacon™, a serverless, user-friendly platform for rapid tertiary analysis of
epigenetic data. In Aim 1, we will develop the EpiBeacon platform using the Amazon Web Services (AWS)
Lambda service to instantly generate heatmaps of chromatin profiling data sourced from ENCODE. EpiBeacon
will be uniquely compatible with the multiple rounds of iterative sampling required for tertiary analysis, and users
will be able to dynamically adjust heatmap parameters and produce publication-ready figures in real time. In Aim
2, we will enable EpiBeacon with more sophisticated comparative analysis capabilities, which we will apply to
answer an emerging problem in the field: whether antibodies and data from Chromatin ImmunoPrecipitation
followed by NGS (ChIP-seq) are applicable to the novel chromatin profiling technology, CUT&RUN. CUT&RUN
has the potential to supersede ChIP-seq as the standard in chromatin profiling, as it produces higher resolution
data with fewer reads and reduced cell input vs. ChIP-seq. However, the methods underlying each approach are
strikingly different, and antibodies that perform well in ChIP-seq may not be successful in CUT&RUN. We will
work with EpiCypher®, a leader in chromatin technology development, to compare H3K4me3 and H3K27me3
antibody performance across ChIP and CUT&RUN experiments. The success of this Aim will validate EpiBeacon
for comparative chromatin analyses and provide essential information for scientists adopting CUT&RUN. In
Phase II, EpiBeacon will be expanded to other analyses (e.g. pathway analysis, motif discovery), other
epigenomic assays (e.g. ATAC-seq), launch new tools to integrate multiple data sets (e.g. ChIP-seq and RNA-
seq), and leverage publicly available datasets (e.g. NCBI SRA), which hold a wealth of epigenetic data that have
been challe...

## Key facts

- **NIH application ID:** 10009580
- **Project number:** 1R43HG011210-01
- **Recipient organization:** BASEPAIR, INC.
- **Principal Investigator:** Amit U Sinha
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $348,442
- **Award type:** 1
- **Project period:** 2020-04-10 → 2021-06-09

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10009580

## Citation

> US National Institutes of Health, RePORTER application 10009580, Realtime visualization and analytics of epigenomic data using a serverless architecture (1R43HG011210-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10009580. Licensed CC0.

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