IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v7y2008i1n16.html
   My bibliography  Save this article

A SNP Streak Model for the Identification of Genetic Regions Identical-by-descent

Author

Listed:
  • Leibon Gregory

    (Dartmouth College)

  • Rockmore Daniel N

    (Dartmouth College)

  • Pollak Martin R

    (Harvard Medical School and Brigham and Women’s Hospital)

Abstract

The availability of very dense genetic maps is changing in a fundamental way the methods used to identify the genetic basis of both rare and common inherited traits. The ability to directly compare the genomes of two related individuals and quickly identify those regions that are inherited identical-by-descent (IBD) from a recent common ancestor would be of utility in a wide range of genetic mapping methods. Here, we describe a simple method for using dense SNP maps to identify regions of the genome likely to be inherited IBD by family members. This method is based on identifying obligate recombination events and examining the pattern of distribution of such events along the genetic map. Specifically, we use the length of a consecutive set of biallelic markers that have a high probability of having avoided such obligate recombination events. This ``SNP streak" is derived from subsets of samples within a pedigree and allows us to make statistical inferences about the ancestry of the region(s) containing stretches of markers with these properties. We show that the use of subsets of more than two samples has the advantage of identifying shorter shared subsegments as significant. This mitigates the effects of errors in SNP calls. We provide specific examples of microarray-based SNP data, using a family with a complex pedigree and with a rare form of inherited kidney disease, to illustrate this approach.

Suggested Citation

  • Leibon Gregory & Rockmore Daniel N & Pollak Martin R, 2008. "A SNP Streak Model for the Identification of Genetic Regions Identical-by-descent," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-19, May.
  • Handle: RePEc:bpj:sagmbi:v:7:y:2008:i:1:n:16
    DOI: 10.2202/1544-6115.1340
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1544-6115.1340
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.2202/1544-6115.1340?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yukinori Okada & Dorothee Diogo & Jeffrey D Greenberg & Faten Mouassess & Walid A L Achkar & Robert S Fulton & Joshua C Denny & Namrata Gupta & Daniel Mirel & Stacy Gabriel & Gang Li & Joel M Kremer &, 2014. "Integration of Sequence Data from a Consanguineous Family with Genetic Data from an Outbred Population Identifies PLB1 as a Candidate Rheumatoid Arthritis Risk Gene," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.

    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:bpj:sagmbi:v:7:y:2008:i:1:n:16. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.