Overcoming the limitations posed by TCRβ repertoire modeling through a GPU-based in-silico DNA recombination algorithm

Gregory Striemer, Harsha Krovi, Ali Akoglu, Benjamin Vincent, Ben Hopson, Jeffrey A Frelinger, Adam Buntzman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The DNA recombination process known as V(D)J recombination is the central mechanism for generating diversity among antigen receptors such as T-cell receptors (TCRs). This diversity is crucial for the development of the adaptive immune system. However, modeling of all the alpha beta TCR sequences is encumbered by the enormity of the potential repertoire, which has been predicted to exceed 10 15 sequences. Prior modeling efforts have, therefore, been limited to extrapolations based on the analysis of minor subsets of the overall TCRbeta repertoire. In this study, we map the recombination process completely onto the graphics processing unit (GPU) hardware architecture using the CUDA programming environment to circumvent prior limitations. For the first time, we present a model of the mouse TCRbeta repertoire to an extent which enabled us to evaluate the Convergent Recombination Hypothesis (CRH) comprehensively at peta-scale level on a single GPU.

Original languageEnglish (US)
Title of host publicationProceedings of the International Parallel and Distributed Processing Symposium, IPDPS
PublisherIEEE Computer Society
Pages231-240
Number of pages10
ISBN (Print)9780769552071
DOIs
StatePublished - 2014
Event28th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2014 - Phoenix, AZ, United States
Duration: May 19 2014May 23 2014

Other

Other28th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2014
CountryUnited States
CityPhoenix, AZ
Period5/19/145/23/14

Fingerprint

T-cells
DNA
Immune system
Antigens
Set theory
Extrapolation
Hardware
Graphics processing unit

Keywords

  • cuda
  • dna
  • gpu
  • recombination
  • t-cell receptors

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Software

Cite this

Striemer, G., Krovi, H., Akoglu, A., Vincent, B., Hopson, B., Frelinger, J. A., & Buntzman, A. (2014). Overcoming the limitations posed by TCRβ repertoire modeling through a GPU-based in-silico DNA recombination algorithm. In Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS (pp. 231-240). [6877258] IEEE Computer Society. https://doi.org/10.1109/IPDPS.2014.34

Overcoming the limitations posed by TCRβ repertoire modeling through a GPU-based in-silico DNA recombination algorithm. / Striemer, Gregory; Krovi, Harsha; Akoglu, Ali; Vincent, Benjamin; Hopson, Ben; Frelinger, Jeffrey A; Buntzman, Adam.

Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS. IEEE Computer Society, 2014. p. 231-240 6877258.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Striemer, G, Krovi, H, Akoglu, A, Vincent, B, Hopson, B, Frelinger, JA & Buntzman, A 2014, Overcoming the limitations posed by TCRβ repertoire modeling through a GPU-based in-silico DNA recombination algorithm. in Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS., 6877258, IEEE Computer Society, pp. 231-240, 28th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2014, Phoenix, AZ, United States, 5/19/14. https://doi.org/10.1109/IPDPS.2014.34
Striemer G, Krovi H, Akoglu A, Vincent B, Hopson B, Frelinger JA et al. Overcoming the limitations posed by TCRβ repertoire modeling through a GPU-based in-silico DNA recombination algorithm. In Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS. IEEE Computer Society. 2014. p. 231-240. 6877258 https://doi.org/10.1109/IPDPS.2014.34
Striemer, Gregory ; Krovi, Harsha ; Akoglu, Ali ; Vincent, Benjamin ; Hopson, Ben ; Frelinger, Jeffrey A ; Buntzman, Adam. / Overcoming the limitations posed by TCRβ repertoire modeling through a GPU-based in-silico DNA recombination algorithm. Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS. IEEE Computer Society, 2014. pp. 231-240
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