Motivation: Analysis of the T-cell receptor repertoire is rapidly entering the general toolbox used by researchers interested in cellular immunity. The annotation of T-cell receptors (TCRs) from raw sequence data poses specific challenges, which arise from the fact that TCRs are not germline encoded, and because of the stochastic nature of the generating process.
Results: In this study, we report the release of Decombinator V4, a tool for the accurate and fast annotation of large sets of TCR sequences. Decombinator was one of the early Python software packages released to analyse the rapidly increasing flow of T-cell receptor repertoire sequence data. The Decombinator package now provides Python 3 compatibility, incorporates improved sequencing error and PCR bias correction algorithms, and provides output which conforms to the international standards proposed by the Adaptive Immune Receptor Repertoire Community.
Availability and implementation: The entire Decombinator suite is freely available at: https://github.com/innate2adaptive/Decombinator.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2020. Published by Oxford University Press.