IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb475/200631.html
   My bibliography  Save this paper

Identification of SNP interactions using logic regression

Author

Listed:
  • Schwender, Holger
  • Ickstadt, Katja

Abstract

Interactions of single nucleotide polymorphisms (SNPs) are assumed to be responsible for complex diseases such as sporadic breast cancer. Important goals of studies concerned with such genetic data are thus to identify combinations of SNPs that lead to a higher risk of developing a disease and to measure the importance of these interactions. There are many approaches based on classification methods such as CART and Random Forests that allow measuring the importance of single variables. But with none of these methods the importance of combinations of variables can be quantified directly. In this paper, we show how logic regression can be employed to identify SNP interactions explanatory for the disease status in a case- control study and propose two measures for quantifying the importance of these interactions for classification. These approaches are then applied, on the one hand, to simulated data sets, and on the other hand, to the SNP data of the GENICA study, a study dedicated to the identification of genetic and gene-environment interactions associated with sporadic breast cancer.

Suggested Citation

  • Schwender, Holger & Ickstadt, Katja, 2006. "Identification of SNP interactions using logic regression," Technical Reports 2006,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200631
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/22675/1/tr31-06.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruczinski, Ingo & Kooperberg, Charles & L. LeBlanc, Michael, 2004. "Exploring interactions in high-dimensional genomic data: an overview of Logic Regression, with applications," Journal of Multivariate Analysis, Elsevier, vol. 90(1), pages 178-195, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Schwender, Holger, 2007. "Minimization of Boolean expressions using matrix algebra," Technical Reports 2007,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Malina Magdalena & Ickstadt Katja & Schwender Holger & Posch Martin & Bogdan Małgorzata, 2014. "Detection of epistatic effects with logic regression and a classical linear regression model," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(1), pages 83-104, 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:zbw:sfb475:200631. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/isdorde.html .

    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.