StructHDP: automatic inference of number of clusters and population structure from admixed genotype data
Author(s) -
Suyash Shringarpure,
Daegun Won,
Eric P. Xing
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr242
Subject(s) - inference , genotype , population , population structure , computer science , computational biology , statistics , biology , artificial intelligence , genetics , mathematics , gene , demography , sociology
Clustering of genotype data is an important way of understanding similarities and differences between populations. A summary of populations through clustering allows us to make inferences about the evolutionary history of the populations. Many methods have been proposed to perform clustering on multilocus genotype data. However, most of these methods do not directly address the question of how many clusters the data should be divided into and leave that choice to the user.
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