title: Current computational methods for prioritizing candidate regulatory polymorphisms.
abstract: Discovery of DNA sequence variants responsible for human phenotypic variation is key to advances in molecular diagnostics and medicines. Historically, variants that alter the protein-coding sequence of genes have been targeted when attempting to identify a trait's etiology; this is done because the rules governing these regions are generally well-understood and candidate variants can be easily selected. However, the effects of variants on gene regulation are increasingly regarded as being as important as protein-coding variation in uncovering the nature of phenotypic variation. I discuss resources and methodology that have recently been developed to computationally prioritize variants that may alter gene expression.
authors.affiliation: Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.
authors.forename: Stephen
authors.initials: S
authors.lastname: Montgomery
mesh_terms: D000483:Alleles; D001665:Binding Sites / Q000235:genetics; D019295:Computational Biology; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D005786:Gene Expression Regulation; D005787:Gene Frequency; D014644:Genetic Variation; D006801:Humans; D011110:Polymorphism, Genetic; D020641:Polymorphism, Single Nucleotide; D022661:RNA, Untranslated / Q000235:genetics; D012984:Software; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D022661:RNA, Untranslated; D014157:Transcription Factors