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The possibilities of using biological knowledge for filtering pairs of SNPs in GWAS studies: an exploratory study on public protein-interaction and pathway data.

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00074889" target="_blank" >RIV/00216224:14330/14:00074889 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004915002590264" target="_blank" >http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004915002590264</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5220/0004915002590264" target="_blank" >10.5220/0004915002590264</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The possibilities of using biological knowledge for filtering pairs of SNPs in GWAS studies: an exploratory study on public protein-interaction and pathway data.

  • Original language description

    Genome-wide association studies have become a standard way of discovering novel causative alleles by loooking for statisticaly significant associations in patient genotyping data. The present challenge for these methods is to discover associations involving multiple interacting loci, a common phenomenon in diseases often related to epistasis. The main problem is the exponential increase in necessary computational power for every additional interacting locus considered in association tests. Several approaches have been proposed to manage this problem, including limiting analysis to interacting pairs and filtering SNPs according to external biological knowledge. Here we explore the possibilities of using public protein interaction data and pathway maps to filter out only pairs of SNPs that are likely to interact, perhaps because of epistatic mechanisms working at the protein level.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/7E13011" target="_blank" >7E13011: THALAssaemia MOdular Stratification System for personalized therapy of beta-thalassemia</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms

  • ISBN

    9789897580123

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    259-264

  • Publisher name

    SciTePress

  • Place of publication

    Angers, France

  • Event location

    Angers, FR

  • Event date

    Mar 3, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article