tcrdist3 0.2.0

flexible distance measures for comparing T cell receptors

tcrdist3

Flexible distance measures for comparing T cell receptors

tcrdist3 is a python API-enabled toolkit for analyzing T-cell receptor repertoires. Some of the functionality and code is adapted from the original tcr-dist package which was released with the publication of Dash et al. Nature (2017) doi:10.1038/nature22383. This package contains a new API for computing tcrdistance measures as well as new features for biomarker development (bioRxiv (2020)). The package has been expanded to include gamma-delta TCRs; it has also been recoded to increase CPU efficiency using numba, a high-performance just-in-time compiler.

Installation

pip install tcrdist3

or

pip install git+https://github.com/kmayerb/tcrdist3.git@0.2.0

Docker

docker pull quay.io/kmayerb/tcrdist3:0.2.0

Documentation

More documentation can be found at tcrdist3.readthedocs.

Basic Usage

import pandas as pd
from tcrdist.repertoire import TCRrep

df = pd.read_csv("dash.csv")
tr = TCRrep(cell_df = df, 
            organism = 'mouse', 
            chains = ['alpha','beta'], 
            db_file = 'alphabeta_gammadelta_db.tsv')

tr.pw_alpha
tr.pw_beta
tr.pw_cdr3_a_aa
tr.pw_cdr3_b_aa

Citing

TCR meta-clonotypes for biomarker discovery with tcrdist3: quantification of public, HLA-restricted TCR biomarkers of SARS-CoV-2 infection

Mayer-Blackwell K, Schattgen S, Cohen-Lavi L, Crawford JC, Souquette A, Gaevert JA, Hertz T, Thomas PG, Bradley PH, Fiore-Gartland A. bioRxiv (2020).

Quantifiable predictive features define epitope-specific T cell receptor repertoires

Pradyot Dash, Andrew J. Fiore-Gartland, Tomer Hertz, George C. Wang, Shalini Sharma, Aisha Souquette, Jeremy Chase Crawford, E. Bridie Clemens, Thi H. O. Nguyen, Katherine Kedzierska, Nicole L. La Gruta, Philip Bradley & Paul G. Thomas Nature (2017).