Comput. Biol. Med. - Degrees of separation as a statistical tool for evaluating candidate genes.

Tópicos

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Resumo

Selection of candidate genes is an important step in the exploration of complex genetic architecture. The number of gene networks available is increasing and these can provide information to help with candidate gene selection. It is currently common to use the degree of connectedness in gene networks as validation in Genome Wide Association (GWA) and Quantitative Trait Locus (QTL) mapping studies. However, it can cause misleading results if not validated properly. Here we present a method and tool for validating the gene pairs from GWA studies given the context of the network they co-occur in. It ensures that proposed interactions and gene associations are not statistical artefacts inherent to the specific gene network architecture. The CandidateBacon package provides an easy and efficient method to calculate the average degree of separation (DoS) between pairs of genes to currently available gene networks. We show how these empirical estimates of average connectedness are used to validate candidate gene pairs. Validation of interacting genes by comparing their connectedness with the average connectedness in the gene network will provide support for said interactions by utilising the growing amount of gene network information available.

Resumo Limpo

select candid gene import step explor complex genet architectur number gene network avail increas can provid inform help candid gene select current common use degre connected gene network valid genom wide associ gwa quantit trait locus qtl map studi howev can caus mislead result valid proper present method tool valid gene pair gwa studi given context network cooccur ensur propos interact gene associ statist artefact inher specif gene network architectur candidatebacon packag provid easi effici method calcul averag degre separ dos pair gene current avail gene network show empir estim averag connected use valid candid gene pair valid interact gene compar connected averag connected gene network will provid support said interact utilis grow amount gene network inform avail

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