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Nature Research, Nature Methods, 6(7), p. 479-479, 2010

DOI: 10.1038/nmeth0610-479b

Nature Research, Nature Methods, S11(6), p. S6-S12, 2009

DOI: 10.1038/nmeth.1376

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Sense from sequence reads: methods for alignment and assembly

Journal article published in 2009 by Paul Flicek, Ewan Birney ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

The most important first step in understanding next-generation sequencing data is the initial alignment or assembly that determines whether an experiment has succeeded and provides a first glimpse into the results. In parallel with the growth of new sequencing technologies, several algorithms that align or assemble the large data output of today's sequencing machines have been developed. We discuss the current algorithmic approaches and future directions of these fundamental tools and provide specific examples for some commonly used tools.