# Methods for RNA splicing variations detection, quantification, visualization, and association from large heterogeneous datasets

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2021 · $432,541

## Abstract

Abstract
The goal of this research program is to develop methods and tools to analyze large heterogeneous RNA-seq
data sets to better understand RNA splicing. The vast majority of human genes are alternatively spliced and
variation in splicing has been shown to be associated with complex disease risk. Despite the wide spread
adoption of affordable high throughput sequencing, variation in RNA splicing has remained understudied due
to the limitations of short read sequencing data and the computational challenges associated with accurate
transcript-level quantification of gene expression. We propose to develop methods to improve the detection,
quantification, and visualization of complex splicing events. We will further develop methods to identify genetic
variants associated with complex splicing variation and to characterize the mechanisms by which splicing
variation affects complex traits. Importantly, the variations and mechanisms predicted by our methods will be
replicated in independent cohorts and experimentally validated using orthogonal methods. The computational
methods and software we will develop will be applied both to publicly available data and data generated by our
groups. We propose to leverage not only our expertise but also our existing code base and tools. The tools will
support both standalone and cloud based execution for scaling up analysis, and will integrate with existing
tools for downstream analysis.

## Key facts

- **NIH application ID:** 10103827
- **Project number:** 5R01GM128096-04
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Yoseph Barash
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $432,541
- **Award type:** 5
- **Project period:** 2018-05-01 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10103827

## Citation

> US National Institutes of Health, RePORTER application 10103827, Methods for RNA splicing variations detection, quantification, visualization, and association from large heterogeneous datasets (5R01GM128096-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10103827. Licensed CC0.

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