Repository associated with the paper "Inferring and predicting the T-cells repertoire dynamics of healthy individuals"
Each figure is generated thanks to the help of the Jupyter notebook file Figure(i).ipynb. Sketches found in the paper were designed thanks to Apple Keynote.
Python 3
NoisET is a python /3.6 software. It is available on PyPI and can be downloaded and installed through pip:
$ pip install noisetsLibrary requirements : seaborn, scipy, scikit-learn
Data-sets analyzed in this study can be found in the following references:
[1] https://clients.adaptivebiotech.com/pub/healthy-adult-time-course-TCRB for P1, P2 and P7
[2] https://doi.org/10.1073/pnas.1809642115 SRA: PRJNA493983 for P3 and P4.
[3] https://doi.org/10.4049/jimmunol.1600005 SRA: PRJNA316572 for P5 and P8.
[4] https://doi.org/10.7554/eLife.53704 SRA: PRJNA577794 for P6.
[5] https://doi.org/10.1016/j.vaccine.2018.02.027 SRA: SRP111073 for P9.