title: Assembly algorithms for next-generation sequencing data.
abstract: The emergence of next-generation sequencing platforms led to resurgence of research in whole-genome shotgun assembly algorithms and software. DNA sequencing data from the Roche 454, Illumina/Solexa, and ABI SOLiD platforms typically present shorter read lengths, higher coverage, and different error profiles compared with Sanger sequencing data. Since 2005, several assembly software packages have been created or revised specifically for de novo assembly of next-generation sequencing data. This review summarizes and compares the published descriptions of packages named SSAKE, SHARCGS, VCAKE, Newbler, Celera Assembler, Euler, Velvet, ABySS, AllPaths, and SOAPdenovo. More generally, it compares the two standard methods known as the de Bruijn graph approach and the overlap/layout/consensus approach to assembly.
authors.affiliation: J. Craig Venter Institute, Rockville, MD 20850-3343, USA. jmiller@jcvi.org
authors.forename: Jason R
authors.initials: JR
authors.lastname: Miller
authors.forename: Sergey
authors.initials: S
authors.lastname: Koren
authors.forename: Granger
authors.initials: G
authors.lastname: Sutton
mesh_terms: D000465:Algorithms; D005544:Forecasting; D017422:Sequence Analysis, DNA / Q000379:methods / Q000639:trends*; D012984:Software