Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1126/science.aam9309 |
Quantitative analysis of population-scale family trees with millions of relatives | |
Kaplanis, Joanna1,2; Gordon, Assaf1,2; Shor, Tal3,4; Weissbrod, Omer5; Geiger, Dan4; Wahl, Mary1,2,6; Gershovits, Michael2; Markus, Barak2; Sheikh, Mona2; Gymrek, Melissa1,2,7,8,9; Bhatia, Gaurav10,11; MacArthur, Daniel G.7,9,10; Price, Alkes L.10,11,12; Erlich, Yaniv1,2,3,13,14 | |
2018-04-13 | |
发表期刊 | SCIENCE
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ISSN | 0036-8075 |
EISSN | 1095-9203 |
出版年 | 2018 |
卷号 | 360期号:6385页码:171-175 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Israel |
英文摘要 | Family trees have vast applications in fields as diverse as genetics, anthropology, and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. We collected 86 million profiles from publicly available online data shared by genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of human longevity and to provide insights into the geographical dispersion of families. We also report a simple digital procedure to overlay other data sets with our resource. |
领域 | 地球科学 ; 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000429805400039 |
WOS关键词 | GENE INTERACTIONS ; HUMAN LONGEVITY ; COMPLEX TRAITS ; LIFE-SPAN ; HERITABILITY ; ASSOCIATION ; HISTORY ; FERTILITY ; EPISTASIS ; ERA |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/198416 |
专题 | 地球科学 资源环境科学 气候变化 |
作者单位 | 1.New York Genome Ctr, New York, NY 10013 USA; 2.Whitehead Inst Biomed Res, 9 Cambridge Ctr, Cambridge, MA 02142 USA; 3.MyHeritage, IL-6037606 Or Yehuda, Israel; 4.Technion Israel Inst Technol, Comp Sci Dept, IL-3200003 Haifa, Israel; 5.Weizmann Inst Sci, Comp Sci Dept, IL-7610001 Rehovot, Israel; 6.Harvard Univ, Dept Mol & Cellular Biol, Cambridge, MA 02138 USA; 7.Harvard Med Sch, Boston, MA 02115 USA; 8.Harvard MIT Program Hlth Sci & Technol, Cambridge, MA 02142 USA; 9.Massachusetts Gen Hosp, Analyt & Translat Genet Unit, Boston, MA 02114 USA; 10.Broad Inst MIT & Harvard, Program Med & Populat Genet, Cambridge, MA 02142 USA; 11.Harvard Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA; 12.Harvard Sch Publ Hlth, Dept Epidemiol, Boston, MA USA; 13.Columbia Univ, Dept Comp Sci, Fu Fdn Sch Engn, New York, NY 10027 USA; 14.Columbia Univ, Dept Syst Biol, Ctr Computat Biol & Bioinformat, New York, NY 10027 USA |
推荐引用方式 GB/T 7714 | Kaplanis, Joanna,Gordon, Assaf,Shor, Tal,et al. Quantitative analysis of population-scale family trees with millions of relatives[J]. SCIENCE,2018,360(6385):171-175. |
APA | Kaplanis, Joanna.,Gordon, Assaf.,Shor, Tal.,Weissbrod, Omer.,Geiger, Dan.,...&Erlich, Yaniv.(2018).Quantitative analysis of population-scale family trees with millions of relatives.SCIENCE,360(6385),171-175. |
MLA | Kaplanis, Joanna,et al."Quantitative analysis of population-scale family trees with millions of relatives".SCIENCE 360.6385(2018):171-175. |
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