# Methods for improving clinical diagnostic by detection, prediction, interpretation and prioritization of aberrant transcriptome variations

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2020 · $347,736

## Abstract

The goal of this research program project is to develop methods to improve clinical diagnosis of children with
rare Mendelian disorders. Even with the most advanced standard-of-care genetic test of exome sequencing (ES)
diagnostic rate is still below 50%. One reason for this rate is that mutations in non-protein coding regions or
those that are synonymous (code for the same protein) are generally discarded even though these could be
deleterious due to their effect on the processing of RNA transcribed from the underlying gene. We propose 2
complementary methods to help improve clinical diagnosis: The first is “RNA-first”, where our algorithms suggest
which clinically accessible tissue (CAT) to use for RNA sequencing, then compare the results to a larger pool of
donors to detect which RNA processing variations may be deleterious. The second is a “DNA-first” approach
where we develop “RNA splicing code” models that predict the effect of genetic variations on RNA processing in
a given tissue of interest. The two approaches, “RNA-first” and “DNA-first”, will be combined into a clinical
diagnostic pipeline at the Children Hospital of Philadelphia (CHOP) and applied to solve undiagnosed cases at
CHOP and other centers, including the NIH’s Undiagnosed Disease Network (UDN).

## Key facts

- **NIH application ID:** 10033447
- **Project number:** 1R01LM013437-01
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Yoseph Barash
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $347,736
- **Award type:** 1
- **Project period:** 2020-08-03 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10033447

## Citation

> US National Institutes of Health, RePORTER application 10033447, Methods for improving clinical diagnostic by detection, prediction, interpretation and prioritization of aberrant transcriptome variations (1R01LM013437-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10033447. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*