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

D 2014

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

LEXA, Matej a Stanislav ŠTEFANIČ

Základní údaje

Originální název

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

Autoři

LEXA, Matej (703 Slovensko, garant, domácí) a Stanislav ŠTEFANIČ (703 Slovensko, domácí)

Vydání

Angers, France, Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, od s. 259-264, 6 s. 2014

Nakladatel

SciTePress

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Francie

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Kód RIV

RIV/00216224:14330/14:00074889

Organizační jednotka

Fakulta informatiky

ISBN

978-989-758-012-3

DOI

http://dx.doi.org/10.5220/0004915002590264

Klíčová slova anglicky

GWAS; SNPs; biological knowledge; databases; genotyping; filtering

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 5. 10. 2014 16:02, doc. Ing. Matej Lexa, Ph.D.

Anotace

V originále

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. After filtering all possible pairs of SNPs by their presence in a common protein-protein interaction or proteins sharing a metabolic or signalling pathway, we calculate the possible reduction in computational requirements under different scenarios. We discuss these exploratory results in the context of the so-called "lost heredity" and the usefulness of similar approach for similar scenarios.

Návaznosti

7E13011, projekt VaV

Název: THALAssaemia MOdular Stratification System for personalized therapy of beta-thalassemia (Akronym: THALAMOSS)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, THALAssaemia MOdular Stratification System for personalized therapy of beta-thalassemia

Citovat

LEXA, Matej a Stanislav ŠTEFANIČ. The possibilities of using biological knowledge for filtering pairs of SNPs in GWAS studies: an exploratory study on public protein-interaction and pathway data. In Oscar Pastor, Christine Sinoquet, Guy Plantier, Tanja Schultz, Ana L. N. Fred, Hugo Gamboa. Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. Angers, France: SciTePress, 2014, s. 259-264. ISBN 978-989-758-012-3. Dostupné z: https://dx.doi.org/10.5220/0004915002590264.

@inproceedings{1139451,
   author = {Lexa, Matej and Štefanič, Stanislav},
   address = {Angers, France},
   booktitle = {Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms},
   doi = {http://dx.doi.org/10.5220/0004915002590264},
   editor = {Oscar Pastor, Christine Sinoquet, Guy Plantier, Tanja Schultz, Ana L. N. Fred, Hugo Gamboa},
   keywords = {GWAS; SNPs; biological knowledge; databases; genotyping; filtering},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Angers, France},
   isbn = {978-989-758-012-3},
   pages = {259-264},
   publisher = {SciTePress},
   title = {The possibilities of using biological knowledge for filtering pairs of SNPs in GWAS studies: an exploratory study on public protein-interaction and pathway data.},
   url = {http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004915002590264},
   year = {2014}
}

TY  - JOUR
ID  - 1139451
AU  - Lexa, Matej - Štefanič, Stanislav
PY  - 2014
TI  - The possibilities of using biological knowledge for filtering pairs of SNPs in GWAS studies: an exploratory study on public protein-interaction and pathway data.
PB  - SciTePress
CY  - Angers, France
SN  - 9789897580123
KW  - GWAS
KW  - SNPs
KW  - biological knowledge
KW  - databases
KW  - genotyping
KW  - filtering
UR  - http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004915002590264
L2  - http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004915002590264
N2  - 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. After filtering all possible pairs of SNPs by their presence in a common protein-protein interaction or proteins sharing a metabolic or signalling pathway, we calculate the possible reduction in computational requirements under different scenarios. We discuss these exploratory results in the context of the so-called "lost heredity" and the usefulness of similar approach for similar scenarios.
ER  -

LEXA, Matej a Stanislav ŠTEFANIČ. The possibilities of using biological knowledge for filtering pairs of SNPs in GWAS studies: an exploratory study on public protein-interaction and pathway data. In Oscar Pastor, Christine Sinoquet, Guy Plantier, Tanja Schultz, Ana L. N. Fred, Hugo Gamboa. \textit{Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms}. Angers, France: SciTePress, 2014, s.~259-264. ISBN~978-989-758-012-3. Dostupné z: https://dx.doi.org/10.5220/0004915002590264.

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