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      BS-Seeker3: ultrafast pipeline for bisulfite sequencing

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      1 , 2 , 1 , 1 ,
      BMC Bioinformatics
      BioMed Central

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          Abstract

          Background

          DNA methylation is an important epigenetic modification critical in regulation and transgenerational inheritance. The methylation level can be estimated at single-nucleotide resolution by whole-genome bisulfite sequencing (BS-seq; WGBS). Current bisulfite aligners provide pipelines for processing the reads by WGBS; however, few are able to analyze the BS-seqs in a reasonable timeframe that meets the needs of the rapid expansion of epigenome sequencing in biomedical research.

          Results

          We introduce BS-Seeker3, an extensively improved and optimized implementation of BS-Seeker2 that leverages the available computational power of a standard bioinformatics lab. BS-Seeker3 adopts all alignment features of BS-Seeker2. It performs ultrafast alignments and achieves both high accuracy and high mappability, more than twice that of the other aligners that we evaluated. Moreover, BS Seeker 3 is well linked with downstream analyzer MethGo for up to 9 types of genomic and epigenomic analyses.

          Conclusions

          BS-Seeker3 is an accurate, versatile, ultra-fast pipeline for processing bisulfite-converted reads. It also helps the user better visualize the methylation data.

          Electronic supplementary material

          The online version of this article (10.1186/s12859-018-2120-7) contains supplementary material, which is available to authorized users.

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          Most cited references2

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          On-line construction of suffix trees

          E Ukkonen (1995)
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            BRAT-nova: fast and accurate mapping of bisulfite-treated reads.

            In response to increasing amounts of sequencing data, faster and faster aligners need to become available. Here, we introduce BRAT-nova, a completely rewritten and improved implementation of the mapping tool BRAT-BW for bisulfite-treated reads (BS-Seq). BRAT-nova is very fast and accurate. On the human genome, BRAT-nova is 2-7 times faster than state-of-the-art aligners, while maintaining the same percentage of uniquely mapped reads and space usage. On synthetic reads, BRAT-nova is 2-8 times faster than state-of-the-art aligners while maintaining similar mapping accuracy, methylation call accuracy, methylation level accuracy and space efficiency.
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              Author and article information

              Contributors
              khuang28@jhu.edu
              chris115135@gmail.com
              paoyang@gate.sinica.edu.tw
              Journal
              BMC Bioinformatics
              BMC Bioinformatics
              BMC Bioinformatics
              BioMed Central (London )
              1471-2105
              3 April 2018
              3 April 2018
              2018
              : 19
              : 111
              Affiliations
              [1 ]ISNI 0000 0001 2287 1366, GRID grid.28665.3f, Institute of Plant and Microbial Biology, Academia Sinica, ; Taipei, Taiwan
              [2 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Biomedical Engineering, , Johns Hopkins University, ; Baltimore, MD USA
              Author information
              http://orcid.org/0000-0002-7402-3075
              Article
              2120
              10.1186/s12859-018-2120-7
              5883884
              29614954
              15ee2baa-4948-426a-9101-aa9d1ec6618a
              © The Author(s). 2018

              Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

              History
              : 4 July 2017
              : 21 March 2018
              Funding
              Funded by: FundRef http://dx.doi.org/10.13039/501100004663, Ministry of Science and Technology, Taiwan;
              Award ID: MOST-103-2313-B-001-003-MY3
              Award ID: 104-2923-B-001 -003 -MY2
              Award ID: 106-2311-B-001 -035 -MY3
              Award Recipient :
              Categories
              Software
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              © The Author(s) 2018

              Bioinformatics & Computational biology
              Bioinformatics & Computational biology

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