The GNUMAP algorithm: Unbiased probabilistic mapping of oligonucleotides from next-generation sequencing

Nathan L. Clement, Quinn Snell, Mark J. Clement, Peter C. Hollenhorst, Jahnvi Purwar, Barbara J. Graves, Bradley R. Cairns, W. Evan Johnson

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

Motivation: The advent of next-generation sequencing technologies has increased the accuracy and quantity of sequence data, opening the door to greater opportunities in genomic research.Results: In this article, we present GNUMAP (Genomic Next-generation Universal MAPper), a program capable of overcoming two major obstacles in the mapping of reads from next-generation sequencing runs. First, we have created an algorithm that probabilistically maps reads to repeat regions in the genome on a quantitative basis. Second, we have developed a probabilistic Needleman-Wunsch algorithm which utilizes _prb.txt and _int.txt files produced in the Solexa/Illumina pipeline to improve the mapping accuracy for lower quality reads and increase the amount of usable data produced in a given experiment.

Original languageEnglish (US)
Pages (from-to)38-45
Number of pages8
JournalBioinformatics
Volume26
Issue number1
DOIs
StatePublished - Oct 27 2009

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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