TY - JOUR T1 - Quantitative analysis of population-scale family trees using millions of relatives JF - bioRxiv DO - 10.1101/106427 SP - 106427 AU - Joanna Kaplanis AU - Assaf Gordon AU - Mary Wahl AU - Michael Gershovits AU - Barak Markus AU - Mona Sheikh AU - Melissa Gymrek AU - Gaurav Bhatia AU - Daniel G. MacArthur AU - Alkes L. Price AU - Yaniv Erlich Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/02/07/106427.abstract N2 - Family trees have vast applications in multiple fields from genetics to 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. Here, we collected 86 million profiles from publicly-available online data from 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 longevity by inspecting millions of relative pairs and to provide insights to population genetics theories on the dispersion of families. We also report a simple digital procedure to overlay other datasets with our resource in order to empower studies with population-scale genealogical data.One Sentence Summary Using massive crowd-sourced genealogy data, we created a population-scale family tree resource for scientific studies. ER -