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This is the PRIMUS project ("primus-beta")
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NEW: Download new version with Pedigree Reconstruction at primus.gs.washington.edu This versions is outdated and incomplete. Please visit the new website for the complete version of PRIMUS. We present a method adapted from graph theory that always identifies the maximum set of unrelated individuals in any dataset, and allows weighting parameters to be utilized in unrelated sample selection. PRIMUS reads in user-generated IBD estimates and outputs the maximum possible set of unrelated individuals, given a specified threshold of relatedness. Additional information for preferential selection of individuals may also be utilized. For example, when there are two equally sized maximum sets of unrelated individuals in a network, PRIMUS can preferentially select the set with more affected individuals. Subscribe to the PRIMUS-Users e-mail list for notifications of updates and new versions. Relevant software: http://students.washington.edu/jeanm5/Simulate_IBD_Python.ta
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