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Bioinformatics Advance Access originally published online on June 14, 2005
Bioinformatics 2005 21(16):3394-3400; doi:10.1093/bioinformatics/bti539
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Statistical analysis of antigen receptor spectratype data

Thomas B. Kepler 1,3,*, Min He 1, John K. Tomfohr 1, Blythe H. Devlin 2, Marcella Sarzotti 3 and M. Louise Markert 2,3

1Department of Biostatistics and Bioinformatics, Duke University Durham, NC 27708, USA
2Department of Pediatrics, Duke University Durham, NC 27708, USA
3Department of Immunology, Duke University Durham, NC 27708, USA

*To whom correspondence should be addressed.

Motivation: The effectiveness of vertebrate adaptive immunity depends crucially on the establishment and maintenance of extreme diversity in the antigen receptor repertoire. Spectratype analysis is a method used in clinical and basic immunological settings in which antigen receptor length diversity is assessed as a surrogate for functional diversity. The purpose of this paper is to describe the systematic derivation and application of statistical methods for the analysis of spectratype data.

Results: The basic probability model used for spectratype analysis is the multinomial model with n, the total number of counts, indeterminate. We derive the appropriate statistics and statistical procedures for testing hypotheses regarding differences in antigen receptor distributions and variable repertoire diversity in different treatment groups.

We then apply these methods to spectratype data obtained from several healthy donors to examine the differences between normal CD4+ and CD8+ T cell repertoires, and to data from a thymus transplant patient to examine the development of repertoire diversity following the transplant.

Availability: http://www.duke.edu/~kepler/spa.html

Contact: kepler{at}duke.edu

Received on April 29, 2005; revised on June 8, 2005; accepted on June 9, 2005

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