Sense from sequence reads: methods for alignment and assembly

doi:10.1038/nmeth.1376

Review

. 2009 Nov;6(11 Suppl):S6-S12.

doi: 10.1038/nmeth.1376.

Sense from sequence reads: methods for alignment and assembly

Paul Flicek¹, Ewan Birney

Affiliations

PMID: 19844229
DOI: 10.1038/nmeth.1376

Review

Sense from sequence reads: methods for alignment and assembly

Paul Flicek et al. Nat Methods. 2009 Nov.

. 2009 Nov;6(11 Suppl):S6-S12.

doi: 10.1038/nmeth.1376.

Authors

Paul Flicek¹, Ewan Birney

Affiliation

¹ European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. flicek@ebi.ac.uk

PMID: 19844229
DOI: 10.1038/nmeth.1376

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.

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[1] Bioinformatics. 2001;17 Suppl 1:S225-33 - PubMed

[2] Bioinformatics. 2001;17 Suppl 1:S225-33 - PubMed

[3] Nucleic Acids Res. 1979 Jun 11;6(7):2601-10 - PubMed

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[9] PLoS Comput Biol. 2009 May;5(5):e1000386 - PubMed

[10] PLoS Comput Biol. 2009 May;5(5):e1000386 - PubMed

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Sense from sequence reads: methods for alignment and assembly

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Sense from sequence reads: methods for alignment and assembly

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Abstract

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