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Velvet assembler : ウィキペディア英語版
Velvet assembler

|released = 2008
| discontinued=
| latest release version = 1.2.10
| latest release date =
| latest preview version =
| latest preview date =
| frequently updated =
| programming language =
| operating system = UNIX-based
| platform =
| size =
| language = C
| status = Active
| genre = Bioinformatics
| license = GPL
| website = http://www.ebi.ac.uk/~zerbino/velvet/
}}
Velvet is an algorithm package that has been designed to deal with ''de novo'' genome assembly and short read sequencing alignments. This is achieved through the manipulation of de Bruijn graphs for genomic sequence assembly via the removal of errors and the simplification of repeated regions.〔Zerbino, D. R.; Birney, E. (2008). (“Velvet: de novo assembly using very short reads” ). Retrieved 2013-10-18.〕 Velvet has also been implemented inside of commercial packages, such as Geneious, MacVector and BioNumerics.
==Introduction==
The development of next-generation sequencers (NGS) allowed for increased cost effectiveness on very short read sequencing. The manipulation of de Bruijn graphs as a method for alignment became more realistic but further developments were needed to address issues with errors and repeats. This led to the development of Velvet by Daniel Zerbino and Ewan Birney at the European Bioinformatics Institute in the United Kingdom.
Velvet works by efficiently manipulating de Bruijn graphs through simplification and compression, without the loss of graph information, by converging non-intersecting paths into single nodes. It eliminates errors and resolves repeats by first using an error correction algorithm that merges sequences together. Repeats are then removed from the sequence via the repeat solver that separates paths which share local overlaps.
The combination of short reads and read pairs allows Velvet to resolve small repeats and produce contigs of reasonable length. This application of Velvet can produce contigs with a N50 length of 50 kb on paired-end prokaryotic data and a 3 kb length for regions of mammalian data.

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