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ReHap: an Integrated System for the Haplotype Assembly Problem from Shotgun Sequencing Data

Single nucleotide polymorphism (SNP) is the most common form of DNA
variation. The set of SNPs present in a chromosome (called the
haplotype) is of interest in a wide area of applications in molecular
biology and biomedicine.
Personalized haplotyping of (portions of/all) the chromosomes of individuals
is one of the most promising basic ingredients leading to effective personalized medicine
(including diagnosis, and eventually therapy). Personalized
haplotyping is getting now technically and economically feasible via
steady progress in shotguns sequencing technologies (see e.g. the
1000 genomes project - A deep catalogue of human genetic
variations). One key algorithmic problem in this process is to solve
the  haplotype assembly problem, (also known as  the single
individual haplotyping problem), which is the problem of
reconstructing the two haplotype strings (paternal and maternal)
using the large collection of short fragments produced by the
PCR-based shotgun technology. Although many algorithms for this
problem have been proposed in the literature there has been little
progress on the task of comparing them on a common basis and on
providing support for selecting the best algorithm for the type of
fragments generated by a specific experiment.
In this paper we present ReHap, an easy-to-use AJAX based web tool that
provides a complete experimental environment for comparing five
different assembly algorithms under a variety of parameters setting,
taking as input user generated data and/or providing several
fragment-generation simulation tools.
This is the first published report of a comparison among five
different haplotype assembly algorithms on a common data and
algorithmic framework.
This system can be used by researchers freely at the url: http://bioalgo.iit.cnr.it/rehap/.

Bionformatics 2010, INSTICC (Institute for Systems and Technologies of Information, Control and Communication), Valencia, 2010

Autori IIT:

Tipo: Articolo in Atti di convegno internazionale con referee
Area di disciplina: Computer Science & Engineering

Attività: Biologia computazionale