BatAlign: an incremental method for accurate alignment of sequencing reads

BatAlign: an incremental method for accurate alignment of sequencing reads

Structural variations (SVs) play a crucial role in genetic diversity. However, the alignments of reads near/across SVs are made inaccurate by the presence of polymorphisms. BatAlign is an algorithm that integrated two strategies called ‘Reverse-Alignment’ and ‘Deep-Scan’ to improve the accuracy of r...

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Main Authors: Lim, Jing-Quan, Tennakoon, Chandana, Guan, Peiyong, Sung, Wing-Kin
Format: Online
Language:English
Published: Oxford University Press 2015
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4652746/
id pubmed-4652746
recordtype oai_dc
spelling pubmed-46527462015-11-25 BatAlign: an incremental method for accurate alignment of sequencing reads Lim, Jing-Quan Tennakoon, Chandana Guan, Peiyong Sung, Wing-Kin Methods Online Structural variations (SVs) play a crucial role in genetic diversity. However, the alignments of reads near/across SVs are made inaccurate by the presence of polymorphisms. BatAlign is an algorithm that integrated two strategies called ‘Reverse-Alignment’ and ‘Deep-Scan’ to improve the accuracy of read-alignment. In our experiments, BatAlign was able to obtain the highest F-measures in read-alignments on mismatch-aberrant, indel-aberrant, concordantly/discordantly paired and SV-spanning data sets. On real data, the alignments of BatAlign were able to recover 4.3% more PCR-validated SVs with 73.3% less callings. These suggest BatAlign to be effective in detecting SVs and other polymorphic-variants accurately using high-throughput data. BatAlign is publicly available at https://goo.gl/a6phxB. Oxford University Press 2015-09-18 2015-07-13 /pmc/articles/PMC4652746/ /pubmed/26170239 http://dx.doi.org/10.1093/nar/gkv533 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Lim, Jing-Quan
Tennakoon, Chandana
Guan, Peiyong
Sung, Wing-Kin
spellingShingle Lim, Jing-Quan
Tennakoon, Chandana
Guan, Peiyong
Sung, Wing-Kin
BatAlign: an incremental method for accurate alignment of sequencing reads
author_facet Lim, Jing-Quan
Tennakoon, Chandana
Guan, Peiyong
Sung, Wing-Kin
author_sort Lim, Jing-Quan
title BatAlign: an incremental method for accurate alignment of sequencing reads
title_short BatAlign: an incremental method for accurate alignment of sequencing reads
title_full BatAlign: an incremental method for accurate alignment of sequencing reads
title_fullStr BatAlign: an incremental method for accurate alignment of sequencing reads
title_full_unstemmed BatAlign: an incremental method for accurate alignment of sequencing reads
title_sort batalign: an incremental method for accurate alignment of sequencing reads
description Structural variations (SVs) play a crucial role in genetic diversity. However, the alignments of reads near/across SVs are made inaccurate by the presence of polymorphisms. BatAlign is an algorithm that integrated two strategies called ‘Reverse-Alignment’ and ‘Deep-Scan’ to improve the accuracy of read-alignment. In our experiments, BatAlign was able to obtain the highest F-measures in read-alignments on mismatch-aberrant, indel-aberrant, concordantly/discordantly paired and SV-spanning data sets. On real data, the alignments of BatAlign were able to recover 4.3% more PCR-validated SVs with 73.3% less callings. These suggest BatAlign to be effective in detecting SVs and other polymorphic-variants accurately using high-throughput data. BatAlign is publicly available at https://goo.gl/a6phxB.
publisher Oxford University Press
publishDate 2015
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4652746/
_version_ 1613503856292921344

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