SAP—A Sequence Mapping and Analyzing Program for Long Sequence Reads Alignment and Accurate Variants Discovery

Zheng Sun and Weidong Tian

PLOS ONE, 2012, vol. 7, issue 8, 1-6

Abstract: The third-generation of sequencing technologies produces sequence reads of 1000 bp or more that may contain high polymorphism information. However, most currently available sequence analysis tools are developed specifically for analyzing short sequence reads. While the traditional Smith-Waterman (SW) algorithm can be used to map long sequence reads, its naive implementation is computationally infeasible. We have developed a new Sequence mapping and Analyzing Program (SAP) that implements a modified version of SW to speed up the alignment process. In benchmarks with simulated and real exon sequencing data and a real E. coli genome sequence data generated by the third-generation sequencing technologies, SAP outperforms currently available tools for mapping short and long sequence reads in both speed and proportion of captured reads. In addition, it achieves high accuracy in detecting SNPs and InDels in the simulated data. SAP is available at https://github.com/davidsun/SAP.

Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042887 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 42887&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0042887

DOI: 10.1371/journal.pone.0042887

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().