A pipeline that accurately recovers T cell receptor (TCR) sequences, including rare TCR sequences, from high throughput sequencing data (including barcoded data) even at low coverage. RTCR employs a data-driven statistical model to rectify PCR and sequencing errors in an adaptive manner. Using simulations we demonstrate that RTCR can easily adapt to the error profiles of different types of sequencers and exhibits consistently high recall and high precision even at low coverages where other pipelines perform poorly. Using published real data we show that RTCR accurately resolves sequencing errors and outperforms all other pipelines.

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RTCR classification

RTCR specifications

Software type:
Pipeline
Restrictions to use:
None
Operating system:
Unix/Linux
License:
GNU General Public License version 3.0
Stability:
Stable
Source code URL:
https://github.com/uubram/RTCR
Interface:
Command line interface
Input data:
RTCR takes FastQ files as input.
Programming languages:
C, Python
Computer skills:
Advanced

RTCR support

Maintainer

Credits

Publications

Institution(s)

Theoretical Biology, Utrecht University, Netherlands; Department of Viroscience, Erasmus MC, Rotterdam, Netherlands

Funding source(s)

The VIRGO consortium, which is funded by the Netherlands Genomics Initiative and by the Dutch government (FES0908); the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 317040 (QuanTI)

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