# Use UCSC Xena to promote integration and usage of the KidsFirst, GTEx, and LINCS L1000 data sets

> **NIH NIH R03** · UNIVERSITY OF CALIFORNIA SANTA CRUZ · 2020 · $308,000

## Abstract

ABSTRACT
The NIH Common Fund program has generated a number of transformative data sets containing a wide variety
of multi-dimensional molecular and phenotypic data from human and model organisms. We propose to
promote the integration and widen the usage of selected Common Fund data sets (KidsFirst, GTEx, and
LINCS L1000) using UCSC Xena. UCSC Xena is a web-based high-performance resource for functional
genomics data visualization with a large user base in the cancer genomics research community. Xena is
already a visualization resource for a Common Fund data set, the GTEx transcriptome, which cancer
researchers can use to compare gene expression between tumors and matched normal tissues. Our proposed
work will further widen the usage of the Common Fund data sets by providing the scientific community a
web-based interactive avenue to visualize and explore the data. We also propose to integrate the data with
other cancer genomics data for pan-cancer across-tissue comparison to identify target genes and pathways in
patients tumors. Lastly our proposal will extend Xena Browser software functionality to use differential gene
expression and leverage external tools and APIs to search for small molecules that might inhibit tumor growth.
We propose the following aims. Aim 1. We will add KidsFirst data to Xena and integrate it with the cancer
genomics data already on Xena to enable comparative visualization of molecular profiles across pediatric and
adult tumors. Aim 2. Building upon the success of the UCSC RNA-seq compendium, we will deliver an even
larger uniformly analyzed RNA-seq data compendium of over 25,0000 samples from KidsFirst, GTEx, TCGA,
TARGET, CCLE and other studies. We will openly-share the compendium data using the Xena Browser. This
rich data resource will support not only users wishing to compare expression across tumor to normal tissues,
but will also support the Treehouse Childhood Cancer initiative in their quest to find treatments for children with
cancer. Aim 3. We will extend Xena software functionality to perform genome-wide differential gene
expression analysis and connect the analysis results to L1000FWD, a state-of-the-art web-based search and
visualization tool for tens of thousands of small-molecule perturbation signatures profiled by the LINCS L1000
assay. This new feature and connectivity will enable users to predict candidate small molecule perturbations
that might disrupt tumor growth using the reverse tumor gene expression signature they identified on Xena.

## Key facts

- **NIH application ID:** 10110706
- **Project number:** 1R03OD030602-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA SANTA CRUZ
- **Principal Investigator:** JINGCHUN ZHU
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $308,000
- **Award type:** 1
- **Project period:** 2020-09-15 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10110706

## Citation

> US National Institutes of Health, RePORTER application 10110706, Use UCSC Xena to promote integration and usage of the KidsFirst, GTEx, and LINCS L1000 data sets (1R03OD030602-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10110706. Licensed CC0.

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