Genome-wide association studies

Genome-wide association studies (GWAS) test hundreds of thousands genetic variants across many genomes to find those statistically associated with a specific trait or disease. This methodology has generated myriad robust associations for range traits and diseases, the number is expected grow steadily as GWAS sample sizes increase. results have applications, such gaining insight into phenotype’s underlying biology, estimating its heritability, calculating correlations, making clinical risk predictions, informing drug development programmes inferring potential causal relationships between factors health outcomes. In this Primer, we provide reader an introduction GWAS, explaining their statistical basis how they are conducted, describe state-of-the art approaches discuss limitations challenges, concluding overview current future applications results. Uffelmann et al. key considerations best practices conducting genome-wide (GWAS), techniques deriving functional inferences from in understanding disease architecture. The Primer also provides information on data sharing discusses important ethical when considering populations data.