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Activity Number: 703
Type: Contributed
Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #319872
Title: A Clustering Algorithm for Human Genetic Data
Author(s): Jae Brodsky* and Teresa Webster and Dorothy Oliver and Jeremy Gollub and Barry Eynon
Companies: Thermo Fisher Scientific and Thermo Fisher Scientific and Thermo Fisher Scientific and Thermo Fisher Scientific and Thermo Fisher Scientific
Keywords: genomics ; clustering ; genotype ; SNP ; human
Abstract:

With the introduction of large genetic studies that interrogate many thousands of positions across the human genome, many markers have produced more than the three genotype clusters expected from biallelic SNPs. While some complicated genetic structures such as copy number variation (CNV) and multi-allelic markers are known to produce data with features beyond the standard three-cluster architecture, other patterns with unknown causes have appeared consistently in human genetic data as well. These multi-cluster data spaces must be identified as having more than three clusters, and the complex clusters must be located correctly. These clusters may take any size, shape, or position in the genotyping space. We have developed a clustering algorithm that addresses these clustering issues, while allowing the freedom necessary to handle unknown cluster size, shape, and position.


Authors who are presenting talks have a * after their name.

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