Development of a novel clustering tool for linear peptide sequences.

ABSTRACT: Epitopes identified in large-scale screens of overlapping peptides often share significant levels of sequence identity, complicating the analysis of epitope-related data. Clustering algorithms are often used to facilitate these analyses, but available methods are generally insufficient in their capacity to define biologically meaningful epitope clusters in the context of the immune response. To fulfil this need we developed an algorithm that generates epitope clusters based on representative or consensus sequences. This tool allows the user to cluster peptide sequences on the basis of a specified level of identity by selecting among three different method options. These include the 'clique method', in which all members of the cluster must share the same minimal level of identity with each

SUBMITTER: Dhanda SK 

PROVIDER: S-EPMC6187223 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature