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Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. | LitMetric

Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data.

Bioinformatics

Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Department of Pathology, Yale University School of Medicine, New Haven, CT 06511, USA and.

Published: October 2015

AI Article Synopsis

  • - Advances in sequencing technology enable detailed studies of B cell immunoglobulin (Ig) repertoires, but challenges arise from the high diversity of Ig genes, necessitating specialized computational approaches.
  • - Change-O is a software suite designed to analyze large Ig repertoire sequencing data, providing tools for tasks like identifying gene segment alleles, partitioning sequences into clonal groups, and assessing repertoire diversity and selection pressure.
  • - The Change-O tools are available for free for non-commercial use and can be downloaded from a specified website, facilitating integrated analyses of Ig sequencing data.

Article Abstract

Unlabelled: Advances in high-throughput sequencing technologies now allow for large-scale characterization of B cell immunoglobulin (Ig) repertoires. The high germline and somatic diversity of the Ig repertoire presents challenges for biologically meaningful analysis, which requires specialized computational methods. We have developed a suite of utilities, Change-O, which provides tools for advanced analyses of large-scale Ig repertoire sequencing data. Change-O includes tools for determining the complete set of Ig variable region gene segment alleles carried by an individual (including novel alleles), partitioning of Ig sequences into clonal populations, creating lineage trees, inferring somatic hypermutation targeting models, measuring repertoire diversity, quantifying selection pressure, and calculating sequence chemical properties. All Change-O tools utilize a common data format, which enables the seamless integration of multiple analyses into a single workflow.

Availability And Implementation: Change-O is freely available for non-commercial use and may be downloaded from http://clip.med.yale.edu/changeo.

Contact: steven.kleinstein@yale.edu.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4793929PMC
http://dx.doi.org/10.1093/bioinformatics/btv359DOI Listing

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