Project Details
Description
Goals: This project will contribute novel bioinformatics approaches for integrative analysis of isoform-level gene expression and gene regulation. The developed methods will facilitate analysis of data across different platforms in the context of expert knowledge about cis-regulatory promoter architecture, gene function and experimental results, using statistically rigorous innovative data-mining methods.
Specific aims of Dr. Justin Starren’s sub-contract are:
Aim 1: Develop novel statistical methods for feature selection and clustering of samples (e.g., tumor samples) based on isoform-level gene expression data from different transcriptome platforms (e.g., exon-array and RNA-seq platforms). The proposed methods will explicitly address the issue of platform bias to accurately normalize and integrate gene expression data at the transcript isoform level.
Dr. Justin Starren group (Northwestern University) will participate in completion of the above Aim. Specifically, Mr. Yanrong Ji, DGP graduate student will continue to work in the joint mentorship of Drs. Starren and Davuluri towards completion of the above aim. The application of the developed methods in this aim will be used to perform sequence analysis, interpretation and correlation with phenotypic outcomes.
Status | Finished |
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Effective start/end date | 6/15/20 → 4/30/21 |
Funding
- State University of New York at Stony Brook (89574/2/1164547 // 7R01LM01129709)
- National Library of Medicine (89574/2/1164547 // 7R01LM01129709)
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