Quantitative analysis of population-scale family trees with millions of relatives

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 pu...

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Bibliographic Details
Published inScience (American Association for the Advancement of Science) Vol. 360; no. 6385; pp. 171 - 175
Main Authors Kaplanis, Joanna, Gordon, Assaf, Shor, Tal, Weissbrod, Omer, Geiger, Dan, Wahl, Mary, Gershovits, Michael, Markus, Barak, Sheikh, Mona, Gymrek, Melissa, Bhatia, Gaurav, MacArthur, Daniel G, Price, Alkes L, Erlich, Yaniv
Format Journal Article
LanguageEnglish
Published United States The American Association for the Advancement of Science 13.04.2018
Subjects
Anthropology
Architecture
Data Use
Datasets as Topic
Family
Family (Sociological Unit)
Family trees
Genealogy
Genealogy and Heraldry
Genetic diversity
Genetic effects
Genetics
Heredity
Heritability
Humans
Life span
Longevity
Migration
Migration Patterns
Models, Genetic
Pedigree
Population
Quantitative analysis
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Summary: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.
Bibliography:ObjectType-Article-1
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These authors equally contributed to this manuscript.
ISSN:0036-8075
1095-9203
1095-9203
DOI:10.1126/science.aam9309