Accurate automated clustering of two-dimensional data for single-nucleotide polymorphism genotyping by a combination of clustering methods: evaluation by large-scale real data
1 Laboratory for Statistical Analysis, Waseda University Shinjuku, Tokyo, Japan
2 Laboratory of SNP Analysis, Waseda University Shinjuku, Tokyo, Japan
3 Laboratory of Pharmacogenetics, RIKEN SNP Research Center, Waseda University Shinjuku, Tokyo, Japan
4 Department of Computer Science, Waseda University Shinjuku, Tokyo, Japan
5 Institute of Medical Science, University of Tokyo Tokyo, Japan
6 Institute of Rheumatology, Tokyo Women's Medical University Tokyo, Japan
*To whom correspondence should be addressed.
| Abstract |
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Motivation: The Invader assay is a fluorescence-based high-throughput genotyping technology. If the output data from the Invader assay were classified automatically, then genotypes for individuals would be determined efficiently. However, existing classification methods do not necessarily yield results with the same accuracy as can be achieved by technicians. Our clustering algorithm, Genocluster, is intended to increase the proportion of data points that need not be manually corrected by technicians.
Results: Genocluster worked well even when the number of clusters was unknown in advance and when there were only a few points in a cluster. The use of Genocluster enabled us to achieve an acceptance rate (proportion of assay results that did not need to be corrected by expert technicians) of 84.4% and a proportion of uncorrected points of 95.8%, as determined using the data from over 31 million points.
Availability: Information for obtaining the executable code, example data and example analysis are available at http://www.genstat.net/genocluster
Contact: kamatani{at}ior.twmu.ac.jp
Associate Editor: Alfonso Valencia
Received on September 20, 2005; revised on March 30, 2006; accepted on March 31, 2006