A note on phasing long genomic regions using local haplotype predictions.
The common approaches for haplotype inference from genotype data are targeted toward phasing short genomic regions. Longer regions are often tackled in a heuristic manner, due to the high computational cost. Here, we describe a novel approach for phasing genotypes over long regions, which is based on combining information from local predictions on short, overlapping regions. The phasing is done in a way, which maximizes a natural maximum likelihood criterion. Among other things, this criterion takes into account the physical length between neighboring single nucleotide polymorphisms. The approach is very efficient and is applied to several large scale datasets and is shown to be successful in two recent benchmarking studies (Zaitlen et al., in press; Marchini et al., in preparation). Our method is publicly available via a webserver at http://research.calit2.net/hap/.
Eskin
Eleazar
E
Computer Science and Engineering, University of California, San Diego, USA. eeskin@cs.ucsd.edu
Sharan
Roded
R
Halperin
Eran
E
D000465:Algorithms; D030541:Databases, Genetic; D015894:Genome, Human; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D016013:Likelihood Functions; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012984:Software