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A Transcriptome Post-Scaffolding Method for Assembling High Quality Contigs ; Computational Biology Journal

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  • معلومة اضافية
    • Contributors:
      Computer Science; Fralin Life Sciences Institute
    • بيانات النشر:
      Hindawi Publishing Corp
    • الموضوع:
      2014
    • Collection:
      VTechWorks (VirginiaTech)
    • نبذة مختصرة :
      With the rapid development of high throughput sequencing technologies, new transcriptomes can be sequenced for little cost with high coverage. Sequence assembly approaches have been modified to meet the requirements for de novo transcriptomes, which have complications not found in traditional genome assemblies such as variation in coverage for each candidate mRNA and alternative splicing. As a consequence, de novo assembly strategies tend to generate a large number of redundant contigs due to sequence variations, which adversely affects downstream analysis and experiments. In this work we proposed TransPS, a transcriptome post-scaffolding method, to generate high quality, nonredundant de novo transcriptomes. TransPS shows promising results on the test transcriptome datasets, where redundancy is greatly reduced by more than 50% and, at the same time, coverage is improved considerably. The web server and source code are available. ; Published version
    • File Description:
      application/pdf; text/xml
    • Relation:
      Mingming Liu, Zach N. Adelman, Kevin M. Myles, and Liqing Zhang, “A Transcriptome Post-Scaffolding Method for Assembling High Quality Contigs,” Computational Biology Journal, vol. 2014, Article ID 961823, 4 pages, 2014. doi:10.1155/2014/961823; http://hdl.handle.net/10919/89571; https://doi.org/10.1155/2014/961823
    • الرقم المعرف:
      10.1155/2014/961823
    • الدخول الالكتروني :
      http://hdl.handle.net/10919/89571
      https://doi.org/10.1155/2014/961823
    • Rights:
      Creative Commons Attribution 4.0 International ; http://creativecommons.org/licenses/by/4.0/ ; Copyright © 2014 Mingming Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    • الرقم المعرف:
      edsbas.E2779985