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Bioinformatics. 2015 Oct 15;31(20):3356-8. doi: 10.1093/bioinformatics/btv359. Epub 2015 Jun 10.

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

Author information

1
Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
2
Department of Pathology, Yale University School of Medicine, New Haven, CT 06511, USA and.
3
Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel.
4
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.

Abstract

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.

PMID:
26069265
PMCID:
PMC4793929
DOI:
10.1093/bioinformatics/btv359
[Indexed for MEDLINE]
Free PMC Article

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