Editorial: Statistical methods, computing, and resources for genome-wide association studies, Volume II

Lide Han; Hailan Liu; Guolian Kang; Min Zhang; Riyan Cheng

doi:10.3389/fgene.2022.1040022

Editorial: Statistical methods, computing, and resources for genome-wide association studies, Volume II

Front Genet. 2022 Oct 20:13:1040022. doi: 10.3389/fgene.2022.1040022. eCollection 2022.

Authors

Lide Han¹, Hailan Liu², Guolian Kang³, Min Zhang⁴, Riyan Cheng⁵

Affiliations

¹ Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States.
² Maize Research Institute, Sichuan Agricultural University, Chengdu, China.
³ Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, United States.
⁴ Department of Statistics, Purdue University, West Lafayette, IN, United States.
⁵ Department of Psychiatry, University of California San Diego, San Diego, CA, United States.

No abstract available

Keywords: binary phenotypes; gene-based testing; genome-wide association studies (GWAS); longitudinal phenotypes; sparse mixture-of-experts models.

Publication types

Editorial