The goal of this project is to enable every biological and biomedical research laboratory to readily and accurately analyze genome structural variation using high-throughput DNA sequence data. We will further develop our existing analysis software. Genome STRIP (Genome STRucture in Populations), to make it into robust, reliable, well-documented, well-supported research software that any biomedical research laboratory can readily adopt. We will enlarge the set of research scenarios in which users can deploy Genome STRIP, so that Genome STRIP can be applied to almost any large-scale sequencing project. We will evolve Genome STRIP'S current capabilities to take advantage of ongoing advances in sequencing technology and to more completely analyze each form of genome structural variation.
We aim to distribute and support research software that enables rigorous, high-quality analysis of genome variation and provides the appropriate data for rigorous analysis of association with disease.
The goal of this project is to enable every biomedical research laboratory to use DNA sequence data to analyze each genome's large-scale """"""""structural"""""""" variants - chromosomal segments that can be missing or present in different numbers of copies in different people's genomes. This work will help scientists to determine the relationships of such variation to disease risk, and to identify genes relevant to each disease.
Handsaker, Robert E; Van Doren, Vanessa; Berman, Jennifer R et al. (2015) Large multiallelic copy number variations in humans. Nat Genet 47:296-303 |