Year: 2009
Type: article
Abstract: Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies.
Source: BMC Proceedings
Authors: Xiang Chen, Meizhuo Zhang, Minghui Wang, Wensheng Zhu, Kelly Cho, Heping Zhang
Institution: Yale University
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,290
OpenAlex ID: W2148023821