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Inference and analysis of haplotypes from combined genotyping studies deposited in dbSNP

¹ Bioinformatics Program, University of California, San Diego, La Jolla, California 92093, USA ² Department of Computer Science, University of California, San Diego, La Jolla, California 92093, USA ³ National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA ⁴ International Computer Science Institute, Berkeley, California 94704, USA

In the attempt to understand human variation and the genetic basis of complex disease, a tremendous number of single nucleotide polymorphisms (SNPs) have been discovered and deposited into NCBI's dbSNP public database. More than 2.7 million SNPs in the database have genotype information. This data provides an invaluable resource for understanding the structure of human variation and the design of genetic association studies. The genotypes deposited to dbSNP are unphased, and thus, the haplotype information is unknown. We applied the phasing method HAP to obtain the haplotype information, block partitions, and tag SNPs for all publicly available genotype data and deposited this information into the dbSNP database. We also deposited the orthologous chimpanzee reference sequence for each predicted haplotype block computed using the UCSC BLASTZ alignments of human and chimpanzee. Using dbSNP, researchers can now easily perform analyses using multiple genotype data sets from the same genomic regions. Dense and sparse genotype data sets from the same region were combined to show that the number of common haplotypes is significantly underestimated in whole genome data sets, while the predicted haplotypes over the common SNPs are consistent between studies. To validate the accuracy of the predictions, we benchmarked HAP's running time and phasing accuracy against PHASE. Although HAP is slightly less accurate than PHASE, HAP is over 1000 times faster than PHASE, making it suitable for application to the entire set of genotypes in dbSNP.

Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.4297805. Freely available online through the Genome Research Immediate Open Access option.

⁵ Corresponding author.
E-mail eeskin{at}cs.ucsd.edu; fax (858) 534-7029.

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