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Quantitative analysis of population-scale family trees with millions of relatives
Author(s) -
Joanna Kaplanis,
Assaf Gordon,
Tal Shor,
Omer Weissbrod,
Dan Geiger,
Mary E. Wahl,
Michael Gershovits,
Barak Markus,
Mona A. Sheikh,
Melissa Gymrek,
Gaurav Bhatia,
Daniel G. MacArthur,
Alkes L. Price,
Yaniv Erlich
Publication year - 2018
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.aam9309
Subject(s) - family tree , data science , population , geography , scale (ratio) , genealogy , scope (computer science) , genetic data , partition (number theory) , resource (disambiguation) , computer science , demography , cartography , sociology , mathematics , history , computer network , combinatorics , programming language
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.

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