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Operating on Genomic Ranges Using BEDOPS

Part of the Methods in Molecular Biology book series (MIMB,volume 1418)

Abstract

The bulk of modern genomics research includes, in part, analyses of large data sets, such as those derived from high resolution, high-throughput experiments, that make computations challenging. The BEDOPS toolkit offers a broad spectrum of fundamental analysis capabilities to query, operate on, and compare quantitatively genomic data sets of any size and number. The toolkit facilitates the construction of complex analysis pipelines that remain efficient in both memory and time by chaining together combinations of its complementary components. The principal utilities accept raw or compressed data in a flexible format, and they provide built-in features to expedite parallel computations.

Key words

  • Bioinformatics
  • Sequencing
  • Algorithm
  • Overlap
  • Genomics
  • Compression
  • Parallelization

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References

  1. Kahn SD (2011) On the future of genomic data. Science 331:728–729

    CAS  CrossRef  PubMed  Google Scholar 

  2. ENCODE Project Consortium (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489:57–74

    CrossRef  Google Scholar 

  3. Neph S, Kuehn MS, Reynolds AP et al (2012) BEDOPS: high-performance genomic feature operations. Bioinformatics 28(14):1919–1920

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  4. Kent WJ, Sugnet CW, Furey TS et al (2002) The human genome browser at UCSC. Genome Res 12:996–1006

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  5. Li H, Handsaker B, Wysoker A et al (2009) The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics 25(16):2078–2079

    CrossRef  PubMed  PubMed Central  Google Scholar 

  6. McIlroy MD, Pinson EN, Tague BA (1978) Unix time-sharing system foreword. Bell Syst Tech J 57(6)

    Google Scholar 

  7. Maurano MT, Humbert R, Rynes E et al (2012) Systematic localization of common disease-associated variation in regulatory DNA. Science 337:1190–1195

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  8. Stergachis AB, Neph S, Reynolds A et al (2013) Developmental fate and cellular maturity encoded in human regulatory DNA landscapes. Cell 154(4):888–903

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  9. Neph S, Vierstra J, Stergachis AB et al (2012) An expansive human regulatory lexicon encoded in transcription factor footprints. Nature 489:83–90

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  10. Thurman RE, Rynes E, Humbert R et al (2012) The accessible chromatin landscape of the human genome. Nature 489:75–82

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  11. Neph S, Stergachis AB, Reynolds A et al (2012) Circuitry and dynamics of human transcription factor regulatory networks. Cell 150(6):1274–1286

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  12. John S, Sabo PJ, Thurman RE et al (2011) Cell-specific chromatin landscapes determine cell-selective glucocorticoid receptor occupancy. Nat Genet 43:264–268

    CAS  CrossRef  PubMed  Google Scholar 

  13. Pollard KS, Hubisz MJ, Rosenbloom KR et al (2010) Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res 20:110–121

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

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Correspondence to John A. Stamatoyannopoulos M.D. .

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Neph, S., Reynolds, A.P., Kuehn, M.S., Stamatoyannopoulos, J.A. (2016). Operating on Genomic Ranges Using BEDOPS. In: Mathé, E., Davis, S. (eds) Statistical Genomics. Methods in Molecular Biology, vol 1418. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3578-9_14

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  • DOI: https://doi.org/10.1007/978-1-4939-3578-9_14

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3576-5

  • Online ISBN: 978-1-4939-3578-9

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