sidhomj/DeepTCR
Deep Learning Methods for Parsing T-Cell Receptor Sequencing (TCRSeq) Data
This tool helps immunologists and genetic researchers analyze T-Cell Receptor (TCR) sequencing data. It takes raw TCR sequences, including paired alpha/beta chains, V/D/J gene usage, and associated HLA information, to identify patterns. The output helps understand T-cell repertoires and their association with various biological conditions, providing insights into immune responses.
122 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to apply deep learning methods to large T-Cell Receptor sequencing datasets to find meaningful patterns or classify repertoires based on sequence characteristics and associated biological data.
Not ideal if you are not working with T-Cell Receptor sequencing data or if you lack access to GPU resources for optimal processing speed.
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122
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44
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 16, 2025
Commits (30d)
0
Dependencies
24
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