Candidate gene association studies : a comprehensive guide to useful in silico tools


Autoria(s): Patnala, Rhadhika; Clements, Judith; Batra, Jyotsna
Data(s)

2013

Resumo

The candidate gene approach has been a pioneer in the field of genetic epidemiology, identifying risk alleles and their association with clinical traits. With the advent of rapidly changing technology, there has been an explosion of in silico tools available to researchers, giving them fast, efficient resources and reliable strategies important to find casual gene variants for candidate or genome wide association studies (GWAS). In this review, following a description of candidate gene prioritisation, we summarise the approaches to single nucleotide polymorphism (SNP) prioritisation and discuss the tools available to assess functional relevance of the risk variant with consideration to its genomic location. The strategy and the tools discussed are applicable to any study investigating genetic risk factors associated with a particular disease. Some of the tools are also applicable for the functional validation of variants relevant to the era of GWAS and next generation sequencing (NGS).

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/63899/

Publicador

BioMed Central

Relação

http://eprints.qut.edu.au/63899/1/63899.pdf

DOI:10.1186/1471-2156-14-39

Patnala, Rhadhika, Clements, Judith, & Batra, Jyotsna (2013) Candidate gene association studies : a comprehensive guide to useful in silico tools. BMC Genetics, 14, p. 39.

http://purl.org/au-research/grants/NHMRC/1050742; 1009458

Direitos

Copyright 2013 the authors.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Fonte

School of Biomedical Sciences; Faculty of Health; Institute of Health and Biomedical Innovation

Palavras-Chave #candidate gene #SNP #LD #in-silico #association studies #cancer
Tipo

Journal Article