Using VAAST to Identify Disease-Associated Variants in Next-Generation Sequencing Data.

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作者： Brett,Kennedy ^[1] ; Zev,Kronenberg ^[2] ; Hao,Hu ^[1] ; Barry,Moore ^[2] ; Steven,Flygare ^[3] ; Martin G,Reese ^[2] ; Lynn B,Jorde ^[1] ; Mark,Yandell ^[1] ; Chad,Huff ^[4]

作者单位： Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah. ^[1] These authors collectively are the first authors of the unit. ^[2] Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas. ^[3] Omicia, Inc, Emeryville, California. ^[4]

关键词 VAAST bioinformatics computational genomics disease-gene identification genome-wide association studies genomics human disease next-generation sequencing rare-variant association test variant classification

主题词病例对照研究(Case-Control Studies);女(雌)性(Female);遗传变异(Genetic Variation);高通量核苷酸序列分析(High-Throughput Nucleotide Sequencing);人类(Humans);男(雄)性(Male);系谱(Pedigree)

DOI 10.1002/0471142905.hg0614s81

PMID 24763993

发布时间 2024-05-07

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