A 2-step penalized regression method for family-based next-generation sequencing association studies

Xiuhua Ding, Shaoyong Su, Kannabiran Nandakumar, Xiaoling Wang, David W. Fardo

Research output: Contribution to journalArticle

3 Scopus citations


Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort.

Original languageEnglish (US)
Article numberS25
JournalBMC Proceedings
Publication statusPublished - Jun 17 2014


ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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