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HapCol: accurate and memory-efficient haplotype assembly from long reads
Author(s) -
Yuri Pirola,
Simone Zaccaria,
Riccardo Dondi,
Gunnar W. Klau,
Nadia Pisanti,
Paola Bonizzoni
Publication year - 2015
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btv495
Subject(s) - computer science , benchmark (surveying) , haplotype , source code , algorithm , data mining , biology , genetics , geodesy , gene , genotype , geography , operating system
Haplotype assembly is the computational problem of reconstructing haplotypes in diploid organisms and is of fundamental importance for characterizing the effects of single-nucleotide polymorphisms on the expression of phenotypic traits. Haplotype assembly highly benefits from the advent of 'future-generation' sequencing technologies and their capability to produce long reads at increasing coverage. Existing methods are not able to deal with such data in a fully satisfactory way, either because accuracy or performances degrade as read length and sequencing coverage increase or because they are based on restrictive assumptions.

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