title: Detecting selection in immunoglobulin sequences.
abstract: The ability to detect selection by analyzing mutation patterns in experimentally derived immunoglobulin (Ig) sequences is a critical part of many studies. Such techniques are useful not only for understanding the response to pathogens, but also to determine the role of antigen-driven selection in autoimmunity, B cell cancers and the diversification of pre-immune repertoires in certain species. Despite its importance, quantifying selection in experimentally derived sequences is fraught with difficulties. The necessary parameters for statistical tests (such as the expected frequency of replacement mutations in the absence of selection) are non-trivial to calculate, and results are not easily interpretable when analyzing more than a handful of sequences. We have developed a web server that implements our previously proposed Focused binomial test for detecting selection. Several features are integrated into the web site in order to facilitate analysis, including V(D)J germline segment identification with IMGT alignment, batch submission of sequences and integration of additional test statistics proposed by other groups. We also implement a Z-score-based statistic that increases the power of detecting selection while maintaining specificity, and further allows for the combined analysis of sequences from different germlines. The tool is freely available at http://clip.med.yale.edu/selection.
authors.affiliation: Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
authors.forename: Mohamed
authors.initials: M
authors.lastname: Uduman
authors.forename: Gur
authors.initials: G
authors.lastname: Yaari
authors.forename: Uri
authors.initials: U
authors.lastname: Hershberg
authors.forename: Jacob A
authors.initials: JA
authors.lastname: Stern
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Shlomchik
authors.forename: Steven H
authors.initials: SH
authors.lastname: Kleinstein
mesh_terms: D000915:Antibody Affinity; D004252:DNA Mutational Analysis; D005803:Genes, Immunoglobulin; D020407:Internet; D012984:Software; D027041:Somatic Hypermutation, Immunoglobulin