Strobe sequence design for haplotype assembly.

TitleStrobe sequence design for haplotype assembly.
Publication TypeJournal Article
Year of Publication2011
AuthorsLo, C, Bashir, A, Bansal, V, Bafna, V
JournalBMC Bioinformatics
Volume12 Suppl 1
PaginationS24
Date Published2011
ISSN1471-2105
iDASH CategoryGenomics
AbstractBACKGROUND: Humans are diploid, carrying two copies of each chromosome, one from each parent. Separating the paternal and maternal chromosomes is an important component of genetic analyses such as determining genetic association, inferring evolutionary scenarios, computing recombination rates, and detecting cis-regulatory events. As the pair of chromosomes are mostly identical to each other, linking together of alleles at heterozygous sites is sufficient to phase, or separate the two chromosomes. In Haplotype Assembly, the linking is done by sequenced fragments that overlap two heterozygous sites. While there has been a lot of research on correcting errors to achieve accurate haplotypes via assembly, relatively little work has been done on designing sequencing experiments to get long haplotypes. Here, we describe the different design parameters that can be adjusted with next generation and upcoming sequencing technologies, and study the impact of design choice on the length of the haplotype. RESULTS: We show that a number of parameters influence haplotype length, with the most significant one being the advance length (distance between two fragments of a clone). Given technologies like strobe sequencing that allow for large variations in advance lengths, we design and implement a simulated annealing algorithm to sample a large space of distributions over advance-lengths. Extensive simulations on individual genomic sequences suggest that a non-trivial distribution over advance lengths results a 1-2 order of magnitude improvement in median haplotype length. CONCLUSIONS: Our results suggest that haplotyping of large, biologically important genomic regions is feasible with current technologies.
DOI10.1186/1471-2105-12-S1-S24
Alternate JournalBMC Bioinformatics
PubMed ID21342554