A computational framework for Bayesian estimation of antigen-driven selection in immunoglobulin sequences based on the analysis of somatic mutation patterns. BASELINe represents a fundamental advance over previous methods by shifting the problem from one of simply detecting selection to one of quantifying selection. Along with providing a more intuitive means to assess and visualize selection, BASELINe allows comparative analysis between groups of sequences derived from different germline V(D)J segments.

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BASELINe forum

No open topic.

BASELINe versioning

No versioning.

BASELINe classification

BASELINe specifications

Software type:
Package
Restrictions to use:
None
Computer skills:
Advanced
Stability:
Stable
Interface:
Command line interface
Operating system:
Unix/Linux
Version:
BASELINe version 1.3

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0 user reviews

0 user reviews

No review has been posted.

BASELINe forum

No open topic.

BASELINe classification

BASELINe specifications

Interface:
Web user interface
Computer skills:
Basic
Stability:
Stable
Restrictions to use:
None
Version:
BASELINe version 1.3

BASELINe support

Maintainer

Credits

Publications

  • (Yaari et al., 2012) Quantifying selection in high-throughput Immunoglobulin sequencing data sets. Nucleic acids research.
    PMID: 22641856
  • (Uduman et al., 2011) Detecting selection in immunoglobulin sequences. Nucleic acids research.
    PMID: 21665923

Institution(s)

Department of Pathology, Yale University School of Medicine, New Haven, CT 06520; and Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA

Funding source(s)

National Institutes of Health (NIH) [R03AI092379-01]; Yale University Biomedical High Performance Computing Center (NIH) [RR19895]

Link to literature

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