biostudies-literatureSitlani CMNIEHS NIH HHSNHLBI NIH HHSNHGRI NIH HHSAmerican Diabetes AssociationNational Institutes of Health1371-1383https://www.ebi.ac.uk/biostudies/studies/S-EPMC8283209biostudies-literatureUnknown30(15)Genome-wide association studies have been successful mapping loci for individual phenotypes, but few studies have comprehensively interrogated evidence of shared genetic effects across multiple phenotypes simultaneously. Statistical methods have been proposed for analyzing multiple phenotypes using summary statistics, which enables studies of shared genetic effects while avoiding challenges associated with individual-level data sharing. Adaptive tests have been developed to maintain power against multiple alternative hypotheses because the most powerful single-alternative test depends on the underlying structure of the associations between the multiple phenotypes and a single nucleotide polymorphism (SNP). Here we compare the performance of six such adaptive tests: two adaptive sum of poweHuman molecular geneticsComparison of adaptive multiple phenotype association tests using summary statistics in genome-wide association studies.PMC8283209T32HL129982U01 HG007416R01 HL134894T32 HL129982R01HL134894T32HL007055R01 ES020836U01HG007416R01 HL142825#1-19-PDF-045R01ES020836R01HL142825T32 HL007055Avery CLSitlani CMBaldassari ARMcKnight BHodonsky CJHighland HMfalseComparison of adaptive multiple phenotype association tests using summary statistics in genome-wide association studies.Genome-wide association studies have been successful mapping loci for individual phenotypes, but few studies have comprehensively interrogated evidence of shared genetic effects across multiple phenotypes simultaneously. Statistical methods have been proposed for analyzing multiple phenotypes using summary statistics, which enables studies of shared genetic effects while avoiding challenges associated with individual-level data sharing. Adaptive tests have been developed to maintain power against multiple alternative hypotheses because the most powerful single-alternative test depends on the underlying structure of the associations between the multiple phenotypes and a single nucleotide polymorphism (SNP). Here we compare the performance of six such adaptive tests: two adaptive sum of powe2021-01-01T00:00:00Z2021 Jul2026-05-30T15:26:04.24Z2025-04-04T10:01:47.771ZS-EPMC82832093394965010.1093/hmg/ddab126