{ "_id": "6adc9ae51f8fc22f6383e8d6", "Package": "SAIGEgds", "Type": "Package", "Title": "Scalable Implementation of Generalized Mixed Models Using GDS\nFiles in Phenome-Wide Association Studies", "Version": "2.13.3", "Date": "2026-09-23", "Authors@R": "c(person(\"Xiuwen\", \"Zheng\", role=c(\"aut\", \"cre\"),\nemail=\"xiuwen.zheng@abbvie.com\", comment=c(ORCID=\"0000-0002-1390-0708\")),\nperson(\"Wei\", \"Zhou\", role=\"ctb\",\ncomment=\"the original author of the SAIGE R package\"),\nperson(\"J. Wade\", \"Davis\", role=\"ctb\"))", "Description": "Scalable implementation of generalized mixed models with\nhighly optimized C++ implementation and integration with\nGenomic Data Structure (GDS) files. It is designed for single\nvariant tests and set-based aggregate tests in large-scale\nPhenome-wide Association Studies (PheWAS) with millions of\nvariants and samples, controlling for sample structure and\ncase-control imbalance. 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