A meta-analysis of genome-wide association studies for serum total IgE in diverse study populations
โ Scribed by Levin, Albert M.; Mathias, Rasika A.; Huang, Lili; Roth, Lindsey A.; Daley, Denise; Myers, Rachel A.; Himes, Blanca E.; Romieu, Isabelle; Yang, Mao; Eng, Celeste; Park, Julie E.; Zoratti, Karla; Gignoux, Christopher R.; Torgerson, Dara G.; Galanter, Joshua M.; Huntsman, Scott; Nguyen, Elizabeth A.; Becker, Allan B.; Chan-Yeung, Moira; Kozyrskyj, Anita L.; Kwok, Pui-Yan; Gilliland, Frank D.; Gauderman, W. James; Bleecker, Eugene R.; Raby, Benjamin A.; Meyers, Deborah A.; London, Stephanie J.; Martinez, Fernando D.; Weiss, Scott T.; Burchard, Esteban G.; Nicolae, Dan L.; Ober, Carole; Barnes, Kathleen C.; Williams, L. Keoki
- Book ID
- 123252001
- Publisher
- Elsevier Science
- Year
- 2013
- Tongue
- English
- Weight
- 490 KB
- Volume
- 131
- Category
- Article
- ISSN
- 1097-6825
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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