Genome-wide association study (GWAS) technology has been a primary method for identifying the genes responsible for diseases and other traits for the past 10 years. Over 2,000 human GWAS reports now appear in the scientific journals. The technology is continuing to improve, and has recently become accessible to researchers studying a wide variety of animals, plants and model organisms. Here, we present an overview of GWAS concepts: the underlying biology, the origins of the method, and the primary components of a GWAS experiment.
Copy number variations have been linked to numerous genetic diseases including cancer, Parkinson's disease, pancreatitis, and lupus. While current best practices for CNV detection often require using microarrays for detecting large CNVs or multiplex ligation-dependent probe amplification (MLPA) for gene-sized CNVs, new methods have been developed with the goal of replacing both of these specialized assays with bioinformatic analysis applied to next-generation sequencing (NGS) data. Because NGS is already used by clinical labs to detect small coding variants, this approach reduces associated costs, resources, and analysis time. This chapter provides an overview of the various approaches to CNV detection via NGS data, and examines VS-CNV, a commercial tool developed by Golden Helix, which provides robust CNV calling capabilities for both gene panel and exome data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.