# Informatics for Functional Integration of Heterogeneous Cancer Genome and Transcriptome Sequencing Data

> **NIH NIH U01** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2021 · $393,250

## Abstract

Project Summary/Abstract
This project aims to develop two novel informatics tools to enable functional integration
of autologous whole exome DNA (WEX) and whole transcriptome RNA sequencing
(WTX) data that are being systematically generated in cancer research and diagnostic
labs. 1) Texomer will deconvolute the tumor genomic and transcriptomic profiles
simultaneously from autologous bulk whole exome (WES) and whole transcriptome
sequencing (WTS) data, and identify functional variants through genome-transcriptome
integrative analysis. It will estimate tumor purity and intra-tumor heterogeneity in both
DNA and RNA data, quantify tumor-allele-specific copy number (ASCN) profiles and
tumor allele-specific expression levels (ASEL), and integrate ASCN and ASEL profiles to
identify functional genomic variants. 2) TransBreak will expand our well-established k-
mer-based assembly approach (novoBreak, Nature Methods 2016) to detect novel
transcriptomic junctions and variants in the tumor WTS data and predict neo-antigens
from assembled novel RNA isoforms. The output of these tools will be thoroughly
evaluated using both computational and experimental means through consortia such as
TCGA and bench/clinical collaborators using established protocols and resources. The
proposed tools will be developed following best software engineering practices and will
be released in open source via publicly available websites.

## Key facts

- **NIH application ID:** 10246262
- **Project number:** 5U01CA247760-02
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Ken Chen
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $393,250
- **Award type:** 5
- **Project period:** 2020-09-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10246262

## Citation

> US National Institutes of Health, RePORTER application 10246262, Informatics for Functional Integration of Heterogeneous Cancer Genome and Transcriptome Sequencing Data (5U01CA247760-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10246262. Licensed CC0.

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