Your browser doesn't support javascript.
loading
Evaluation of GENESIS, SAIGE, REGENIE and fastGWA-GLMM for genome-wide association studies of binary traits in correlated data.
Gurinovich, Anastasia; Li, Mengze; Leshchyk, Anastasia; Bae, Harold; Song, Zeyuan; Arbeev, Konstantin G; Nygaard, Marianne; Feitosa, Mary F; Perls, Thomas T; Sebastiani, Paola.
Afiliación
  • Gurinovich A; Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, United States.
  • Li M; Bioinformatics Program, Boston University, Boston, MA, United States.
  • Leshchyk A; Bioinformatics Program, Boston University, Boston, MA, United States.
  • Bae H; Biostatistics Program, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, United States.
  • Song Z; Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States.
  • Arbeev KG; Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, United States.
  • Nygaard M; Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark.
  • Feitosa MF; Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St Louis, MO, United States.
  • Perls TT; Department of Medicine, Geriatrics Section, Boston University School of Medicine, Boston, MA, United States.
  • Sebastiani P; Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, United States.
Front Genet ; 13: 897210, 2022.
Article en En | MEDLINE | ID: mdl-36212134
Palabras clave
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Genet Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Genet Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos