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    iPAC: A genome-guided assembler of isoforms via phasing and combing paths.

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    Name:
    BIOINF-2019-1908.R1_Proof_hi.pdf
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    495.4Kb
    Format:
    PDF
    Description:
    Accepted manuscript
    Download
    Type
    Article
    Authors
    Yu, Ting
    Liu, Juntao
    Gao, Xin cc
    Li, Guojun
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Structural and Functional Bioinformatics Group
    KAUST Grant Number
    FCC/1/1976-18-01
    FCC/1/1976-23-01
    FCC/1/1976-25-01
    FCC/1/1976-26-01
    Date
    2020-01-27
    Online Publication Date
    2020-01-27
    Print Publication Date
    2020-05-01
    Embargo End Date
    2021-01-28
    Permanent link to this record
    http://hdl.handle.net/10754/661333
    
    Metadata
    Show full item record
    Abstract
    MOTIVATION:Full-length transcript reconstruction is very important and quite challenging for the widely used RNA-seq data analysis. Currently available RNA-seq assemblers generally suffered from serious limitations in practical applications, such as low assembly accuracy and incompatibility with latest alignment tools. RESULTS:We introduce iPAC, a new genome-guided assembler for reconstruction of isoforms, which revolutionizes the usage of paired-end and sequencing depth information via phasing and combing paths over a newly designed phasing graph. Tested on both simulated and real datasets, it is to some extent superior to all the salient assemblers of the same kind. Especially, iPAC is significantly powerful in recovery of lowly expressed transcripts while others are not. AVAILABILITY: iPAC is freely available at http://sourceforge.net/projects/transassembly/files. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
    Citation
    Yu, T., Liu, J., Gao, X., & Li, G. (2020). iPAC: A genome-guided assembler of isoforms via phasing and combing paths. Bioinformatics. doi:10.1093/bioinformatics/btaa052
    Sponsors
    This work was supported by the National Natural Science Foundation of China with codes 11931008, 61801265, 61877064, 31571354 and 61771009, and the Natural Science Foundation of Shandong Province with code ZR2018PA001, and by funding from King Abdullah University of Science and Technology (KAUST), under award number FCC/1/1976-18-01, FCC/1/1976-23-01, FCC/1/1976-25-01, FCC/1/1976-26-01, FCS/1/4102-02-01, and URF/1/4098-01-01. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
    Publisher
    Oxford University Press (OUP)
    Journal
    Bioinformatics
    DOI
    10.1093/bioinformatics/btaa052
    Additional Links
    https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa052/5716327
    ae974a485f413a2113503eed53cd6c53
    10.1093/bioinformatics/btaa052
    Scopus Count
    Collections
    Articles; Structural and Functional Bioinformatics Group; Computer Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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