IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-540-74496-2_30.html
   My bibliography  Save this book chapter

Assessment of Genetic Association using Haplotypes Inferred with Uncertainty via Markov Chain Monte Carlo

In: Monte Carlo and Quasi-Monte Carlo Methods 2006

Author

Listed:
  • Raquel Iniesta

    (Catalan Institute of Oncology, Cancer Epidemiology Service)

  • Victor Moreno

    (Catalan Institute of Oncology, Cancer Epidemiology Service)

Abstract

Summary In the last years, haplotypic information has become an important subject in the context of molecular genetic studies. Assuming that some genetic mutations take part in the etiology of some diseases, it could be of great interest to compare sets of genetic variations among different unrelated individuals, inherited in block from their parents, in order to conclude if there is some association between variations and a disease. The main problem is that, in the absence of family data, obtaining haplotypic information is not straightforward: individuals having more than one polymorphic heterozygous locus have uncertain haplotypes. We have developed a Markov Chain Monte Carlo method to estimate simultaneously the sample frequency of each possible haplotype and the association between haplotypes and a disease.

Suggested Citation

  • Raquel Iniesta & Victor Moreno, 2008. "Assessment of Genetic Association using Haplotypes Inferred with Uncertainty via Markov Chain Monte Carlo," Springer Books, in: Alexander Keller & Stefan Heinrich & Harald Niederreiter (ed.), Monte Carlo and Quasi-Monte Carlo Methods 2006, pages 529-535, Springer.
  • Handle: RePEc:spr:sprchp:978-3-540-74496-2_30
    DOI: 10.1007/978-3-540-74496-2_30
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-540-74496-2_30. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.