IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v52y2008i11p4891-4902.html
   My bibliography  Save this article

A fast haplotype inference method for large population genotype data

Author

Listed:
  • Zhang, Ji-Hong
  • Wu, Ling-Yun
  • Chen, Jian
  • Zhang, Xiang-Sun

Abstract

With the rapid progress of genotyping techniques, many large-scale, genome-wide disease studies are now under way. One of the challenges of large disease-association studies is developing a fast and accurate computing method for haplotype inference from genotype data. In this paper, a new computing method for population-based haplotype inference problem is proposed. The designed method does not assume haplotype blocks in the population and allows each individual haplotype to have its own structure, and thus is able to accommodate recombination and obtain higher adaptivity to the genotype data, specifically in the case of long marker maps. This method develops a dynamic programming algorithm, which is theoretically guaranteed to find exact maximum likelihood solutions of the variable order Markov chain model for haplotype inference problem within linear running time. Hence, it is fast and, as a result, practicable for large genotype datasets. Through extensive computational experiments on large-scale real genotype data, the proposed method is shown to be fast and efficient.

Suggested Citation

  • Zhang, Ji-Hong & Wu, Ling-Yun & Chen, Jian & Zhang, Xiang-Sun, 2008. "A fast haplotype inference method for large population genotype data," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4891-4902, July.
  • Handle: RePEc:eee:csdana:v:52:y:2008:i:11:p:4891-4902
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00209-0
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

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

    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:eee:csdana:v:52:y:2008:i:11:p:4891-4902. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.