Stephanie M Gogarten1, Tamar Sofer2,3, Han Chen4,5, Chaoyu Yu1, Jennifer A Brody6, Timothy A Thornton1, Kenneth M Rice1, Matthew P Conomos1. 1. Department of Biostatistics, University of Washington, Seattle, WA, USA. 2. Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. 3. Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA. 4. Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA. 5. Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA. 6. Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
Abstract
SUMMARY: The Genomic Data Storage (GDS) format provides efficient storage and retrieval of genotypes measured by microarrays and sequencing. We developed GENESIS to perform various single- and aggregate-variant association tests using genotype data stored in GDS format. GENESIS implements highly flexible mixed models, allowing for different link functions, multiple variance components and phenotypic heteroskedasticity. GENESIS integrates cohesively with other R/Bioconductor packages to build a complete genomic analysis workflow entirely within the R environment. AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/GENESIS; vignettes included. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: The Genomic Data Storage (GDS) format provides efficient storage and retrieval of genotypes measured by microarrays and sequencing. We developed GENESIS to perform various single- and aggregate-variant association tests using genotype data stored in GDS format. GENESIS implements highly flexible mixed models, allowing for different link functions, multiple variance components and phenotypic heteroskedasticity. GENESIS integrates cohesively with other R/Bioconductor packages to build a complete genomic analysis workflow entirely within the R environment. AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/GENESIS; vignettes included. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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