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TraCeR

A computational method to reconstruct full-length, paired T cell receptor (TCR) sequences from T lymphocyte single-cell RNA sequence data. TraCeR links T cell specificity with functional response by revealing clonal relationships between cells alongside their transcriptional profiles. TraCeR extracts TCR-derived sequencing reads for each cell by alignment against ‘combinatorial recombinomes’ comprising all possible combinations of V and J segments. Reads are then assembled into contiguous sequences that are analyzed to find full-length, recombined TCR sequences. Importantly, the reconstructed recombinant sequences typically contain nearly the complete length of the TCR V(D)J region and so allow high-confidence discrimination between closely related gene segments. Our method is sensitive, accurate and easy to adapt to any species for which annotated TCR gene sequences are available.

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TraCeR versioning

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TraCeR classification

TraCeR specifications

Software type:
Package/Module
Restrictions to use:
None
Programming languages:
Python
Stability:
Stable
Interface:
Command line interface
Operating system:
Unix/Linux
Computer skills:
Advanced
Maintained:
Yes
Issue URL:
https://github.com/teichlab/tracer/issues

TraCeR support

Maintainer

  • Michael J T Stubbington < >

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Publications

Institution(s)

European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK; Wellcome Trust Sanger Institute, Cambridge, UK

Funding source(s)

This work was supported by European Research Council (grant ThSWITCH, number 260507) and the Lister Institute for Preventative Medicine.

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