Statistical methods of SNP data analysis with applications

Abstract : Various statistical methods important for genetic analysis are considered and developed. Namely, we concentrate on the multifactor dimensionality reduction, logic regression, random forests and stochastic gradient boosting. These methods and their new modifications, e.g., the MDR method with "independent rule", are used to study the risk of complex diseases such as cardiovascular ones. The roles of certain combinations of single nucleotide polymorphisms and external risk factors are examined. To perform the data analysis concerning the ischemic heart disease and myocardial infarction the supercomputer SKIF "Chebyshev" of the Lomonosov Moscow State University was employed.
Type de document :
Pré-publication, Document de travail
2011
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https://hal.archives-ouvertes.fr/hal-00600143
Contributeur : Alexander Bulinski <>
Soumis le : vendredi 24 juin 2011 - 00:02:33
Dernière modification le : mercredi 12 octobre 2016 - 01:01:04
Document(s) archivé(s) le : dimanche 25 septembre 2011 - 02:20:40

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  • HAL Id : hal-00600143, version 1
  • ARXIV : 1106.4989

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INSMI | PMA | UPMC | USPC

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Alexander Bulinski, Oleg Butkovsky, Alexey Shashkin, Pavel Yaskov. Statistical methods of SNP data analysis with applications. 2011. <hal-00600143>

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