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Long-Range Autocorrelations of CpG Islands in the Human Genome

Author

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  • Benjamin Koester
  • Thomas J Rea
  • Alan R Templeton
  • Alexander S Szalay
  • Charles F Sing

Abstract

In this paper, we use a statistical estimator developed in astrophysics to study the distribution and organization of features of the human genome. Using the human reference sequence we quantify the global distribution of CpG islands (CGI) in each chromosome and demonstrate that the organization of the CGI across a chromosome is non-random, exhibits surprisingly long range correlations (10 Mb) and varies significantly among chromosomes. These correlations of CGI summarize functional properties of the genome that are not captured when considering variation in any particular separate (and local) feature. The demonstration of the proposed methods to quantify the organization of CGI in the human genome forms the basis of future studies. The most illuminating of these will assess the potential impact on phenotypic variation of inter-individual variation in the organization of the functional features of the genome within and among chromosomes, and among individuals for particular chromosomes.

Suggested Citation

  • Benjamin Koester & Thomas J Rea & Alan R Templeton & Alexander S Szalay & Charles F Sing, 2012. "Long-Range Autocorrelations of CpG Islands in the Human Genome," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-10, January.
    • Handle: RePEc:plo:pone00:0029889
    DOI: 10.1371/journal.pone.0029889
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    Cited by:

    1. Yanguang Chen, 2020. "New framework of Getis-Ord’s indexes associating spatial autocorrelation with interaction," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-25, July.

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