Idioma:

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

Li, Xihao ; Li, Zilin ; Zhou, Hufeng ; Gaynor, Sheila M ; Liu, Yaowu ; Chen, Han ; Sun, Ryan ; Dey, Rounak ; Arnett, Donna K ; Aslibekyan, Stella ; Ballantyne, Christie M ; Bielak, Lawrence F ; Blangero, John ; Boerwinkle, Eric ; Bowden, Donald W ; Broome, Jai G ; Conomos, Matthew P ; Correa, Adolfo ; Cupples, L Adrienne ; Curran, Joanne E ; Freedman, Barry I ; Guo, Xiuqing ; Hindy, George ; Irvin, Marguerite R ; Kardia, Sharon L R ; Kathiresan, Sekar ; Khan, Alyna T ; Kooperberg, Charles L ; Laurie, Cathy C ; Liu, X Shirley ; Mahaney, Michael C ; Manichaikul, Ani W ; Martin, Lisa W ; Mathias, Rasika A ; McGarvey, Stephen T ; Mitchell, Braxton D ; Montasser, May E ; Moore, Jill E ; Morrison, Alanna C ; O'Connell, Jeffrey R ; Palmer, Nicholette D ; Pampana, Akhil ; Peralta, Juan M ; Peyser, Patricia A ; Psaty, Bruce M ; Redline, Susan ; Rice, Kenneth M ; Rich, Stephen S ; Smith, Jennifer A ; Tiwari, Hemant K ; Tsai, Michael Y ; Vasan, Ramachandran S ; Wang, Fei Fei ; Weeks, Daniel E ; Weng, Zhiping ; Wilson, James G ; Yanek, Lisa R ; Neale, Benjamin M ; Sunyaev, Shamil R ; Abecasis, Gonçalo R ; Rotter, Jerome I ; Willer, Cristen J ; Peloso, Gina M ; Natarajan, Pradeep ; Lin, Xihong

Nature genetics, 2020-09, Vol.52 (9), p.969-983 [Periódico revisado por pares]

United States: Nature Publishing Group

Texto completo disponível

Citações Citado por

Enviar para

Título:
Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale
Autor: Li, Xihao ; Li, Zilin ; Zhou, Hufeng ; Gaynor, Sheila M ; Liu, Yaowu ; Chen, Han ; Sun, Ryan ; Dey, Rounak ; Arnett, Donna K ; Aslibekyan, Stella ; Ballantyne, Christie M ; Bielak, Lawrence F ; Blangero, John ; Boerwinkle, Eric ; Bowden, Donald W ; Broome, Jai G ; Conomos, Matthew P ; Correa, Adolfo ; Cupples, L Adrienne ; Curran, Joanne E ; Freedman, Barry I ; Guo, Xiuqing ; Hindy, George ; Irvin, Marguerite R ; Kardia, Sharon L R ; Kathiresan, Sekar ; Khan, Alyna T ; Kooperberg, Charles L ; Laurie, Cathy C ; Liu, X Shirley ; Mahaney, Michael C ; Manichaikul, Ani W ; Martin, Lisa W ; Mathias, Rasika A ; McGarvey, Stephen T ; Mitchell, Braxton D ; Montasser, May E ; Moore, Jill E ; Morrison, Alanna C ; O'Connell, Jeffrey R ; Palmer, Nicholette D ; Pampana, Akhil ; Peralta, Juan M ; Peyser, Patricia A ; Psaty, Bruce M ; Redline, Susan ; Rice, Kenneth M ; Rich, Stephen S ; Smith, Jennifer A ; Tiwari, Hemant K ; Tsai, Michael Y ; Vasan, Ramachandran S ; Wang, Fei Fei ; Weeks, Daniel E ; Weng, Zhiping ; Wilson, James G ; Yanek, Lisa R ; Neale, Benjamin M ; Sunyaev, Shamil R ; Abecasis, Gonçalo R ; Rotter, Jerome I ; Willer, Cristen J ; Peloso, Gina M ; Natarajan, Pradeep ; Lin, Xihong
Assuntos: Analysis ; Annotations ; Association analysis ; Cholesterol ; Cholesterol, LDL - genetics ; Computer Simulation ; DNA sequencing ; Epigenetics ; Gene sequencing ; Genetic Predisposition to Disease - genetics ; Genetic Variation - genetics ; Genome - genetics ; Genome-Wide Association Study - methods ; Genomes ; Genomics ; Humans ; Lipids ; Lipoproteins ; Low density lipoproteins ; Methods ; Models, Genetic ; Molecular Sequence Annotation - methods ; Nucleotide sequencing ; Phenotype ; Phenotypes ; Population ; Population structure ; Power ; Precision medicine ; Proteins ; Simulation ; Whole genome sequencing ; Whole Genome Sequencing - methods
É parte de: Nature genetics, 2020-09, Vol.52 (9), p.969-983
Notas: X. Li, Z.L., H.Z., G.R.A., J.I.R., C.J.W., G.M.P., P.N. and X. Lin designed the experiments. X. Li, Z.L., H.Z., and X. Lin performed the experiments. X. Li, Z.L., H.Z., S.M.G., Y.L., H.C., R.S., R.D., D.K.A., S.A., C.M.B., L.F.B., J.B., E.B., D.W.B., J.G.B., M.P.C., A.C., L.A.C., J.E.C., B.I.F., X.G., G.H., M.R.I., S.L.R.K., S.K., A.T.K., C.L.K., C.C.L., X.S.L., M.C.M., A.W.M., L.W.M., R.A.M., S.T.M., B.D.M., M.E.M., J.E.M., A.C.M., J.R.O., N.D.P., A.P., J.M.P., P.A.P., B.M.P., S.R., K.M.R., S.S.R., J.A.S., H.K.T., M.Y.T., R.S.V., F.F.W., D.E.W., Z.W., J.G.W., L.R.Y., B.M.N., S.R.S., G.R.A., J.I.R., C.J.W., G.M.P., P.N., and X. Lin acquired, analyzed or interpreted data. G.M.P., P.N., and NHLBI TOPMed Lipids Working Group provided administrative, technical or material support. X. Li, Z.L., S.M.G., J.I.R., G.M.P., P.N., and X. Lin drafted the manuscript and revised according to co-author suggestions. All authors critically reviewed the manuscript, suggested revisions as needed, and approved the final version.
Author contributions
Descrição: Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.
Editor: United States: Nature Publishing Group
Idioma: Inglês

Links

View this record in MEDLINE/PubMed

Voltar para lista de resultados

Anterior Resultado 6 Avançar Ir para próxima página

Realização: Logos de Redes Sociais:

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

United States: Nature Publishing Group

Buscando em bases de dados remotas. Favor aguardar.