title: SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments.
abstract: Identifying which mutation(s) within a given genotype is responsible for an observable phenotype is important in many aspects of molecular biology. Here, we present SigniSite, an online application for subgroup-free residue-level genotype-phenotype correlation. In contrast to similar methods, SigniSite does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set phenotype. As output, SigniSite displays a sequence logo, depicting the strength of the phenotype association of each residue and a heat-map identifying 'hot' or 'cold' regions. SigniSite was benchmarked against SPEER, a state-of-the-art method for the prediction of specificity determining positions (SDP) using a set of human immunodeficiency virus protease-inhibitor genotype-phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found to outperform SPEER. SigniSite is available at: http://www.cbs.dtu.dk/services/SigniSite/.
authors.affiliation: Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Lyngby, Denmark. jessen@cbs.dtu.dk
authors.forename: Leon Eyrich
authors.initials: LE
authors.lastname: Jessen
authors.forename: Ilka
authors.initials: I
authors.lastname: Hoof
authors.forename: Ole
authors.initials: O
authors.lastname: Lund
authors.forename: Morten
authors.initials: M
authors.lastname: Nielsen
mesh_terms: D024882:Drug Resistance, Viral / Q000235:genetics; D056726:Genetic Association Studies / Q000379:methods*; D005838:Genotype; D016333:HIV Protease / Q000235:genetics; D017320:HIV Protease Inhibitors / Q000494:pharmacology; D015497:HIV-1 / Q000187:drug effects / Q000235:genetics; D020407:Internet; D009154:Mutation; D010641:Phenotype; D056510:Position-Specific Scoring Matrices; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein; D012984:Software
chemical_list: D017320:HIV Protease Inhibitors; D016333:HIV Protease