GWAMA: software for genome-wide association meta-analysis
✍ Scribed by Reedik Mägi; Andrew P Morris
- Book ID
- 114999181
- Publisher
- BioMed Central
- Year
- 2010
- Tongue
- English
- Weight
- 488 KB
- Volume
- 11
- Category
- Article
- ISSN
- 1471-2105
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Meta-analysis of genome-wide association studies involves testing single nucleotide polymorphisms (SNPs) using summary statistics that are weighted sums of site-specific score or Wald statistics. This approach avoids having to pool individual-level data. We describe the weights that maximize the pow
## Abstract Genome‐wide association studies have recently identified many new loci associated with human complex diseases. These newly discovered variants typically have weak effects requiring studies with large numbers of individuals to achieve the statistical power necessary to identify them. Lik
Despite the success of genome-wide association studies, much of the genetic contribution to complex human traits is still unexplained. One potential source of genetic variation that may contribute to this “missing heritability” is that which differs in magnitude and/or direction between males and fe