Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.

High-volume sequencing of DNA and RNA is now within reach of any research laboratory and is quickly becoming established as a key research tool. In many workflows, each of the short sequences ("reads") resulting from a sequencing run are first "mapped" (aligned) to a reference se...

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Asıl Yazarlar: Lunter, G, Goodson, M
Materyal Türü: Journal article
Dil:English
Baskı/Yayın Bilgisi: 2011
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author Lunter, G
Goodson, M
author_facet Lunter, G
Goodson, M
author_sort Lunter, G
collection OXFORD
description High-volume sequencing of DNA and RNA is now within reach of any research laboratory and is quickly becoming established as a key research tool. In many workflows, each of the short sequences ("reads") resulting from a sequencing run are first "mapped" (aligned) to a reference sequence to infer the read from which the genomic location derived, a challenging task because of the high data volumes and often large genomes. Existing read mapping software excel in either speed (e.g., BWA, Bowtie, ELAND) or sensitivity (e.g., Novoalign), but not in both. In addition, performance often deteriorates in the presence of sequence variation, particularly so for short insertions and deletions (indels). Here, we present a read mapper, Stampy, which uses a hybrid mapping algorithm and a detailed statistical model to achieve both speed and sensitivity, particularly when reads include sequence variation. This results in a higher useable sequence yield and improved accuracy compared to that of existing software.
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spelling oxford-uuid:881d7083-0c25-4aa7-a03c-764b21a723d32022-03-26T22:14:53ZStampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:881d7083-0c25-4aa7-a03c-764b21a723d3EnglishSymplectic Elements at Oxford2011Lunter, GGoodson, MHigh-volume sequencing of DNA and RNA is now within reach of any research laboratory and is quickly becoming established as a key research tool. In many workflows, each of the short sequences ("reads") resulting from a sequencing run are first "mapped" (aligned) to a reference sequence to infer the read from which the genomic location derived, a challenging task because of the high data volumes and often large genomes. Existing read mapping software excel in either speed (e.g., BWA, Bowtie, ELAND) or sensitivity (e.g., Novoalign), but not in both. In addition, performance often deteriorates in the presence of sequence variation, particularly so for short insertions and deletions (indels). Here, we present a read mapper, Stampy, which uses a hybrid mapping algorithm and a detailed statistical model to achieve both speed and sensitivity, particularly when reads include sequence variation. This results in a higher useable sequence yield and improved accuracy compared to that of existing software.
spellingShingle Lunter, G
Goodson, M
Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.
title Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.
title_full Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.
title_fullStr Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.
title_full_unstemmed Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.
title_short Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.
title_sort stampy a statistical algorithm for sensitive and fast mapping of illumina sequence reads
work_keys_str_mv AT lunterg stampyastatisticalalgorithmforsensitiveandfastmappingofilluminasequencereads
AT goodsonm stampyastatisticalalgorithmforsensitiveandfastmappingofilluminasequencereads