This reporsity contains code and information of data used in the paper “scNAT: A deep learning method for integrating paired single cell RNA and T cell receptor sequencing profiles”. Source code for scNAT are in the scNAT folder, the tutorial is in the tutorials folder.
The use of scNAT to integrate scRNA-seq and scTCR-seq data allows for a more comprehensive analysis that leverages the strengths of both data types. By combining the gene expression information from scRNA-seq with the TCR repertoire diversity and clonality information from scTCR-seq, we can better understand the complex biological processes and identify novel cell subtypes that may have previously gone undetected. A figure summary is shown below.
pip install -i https://test.pypi.org/simple/ scNAT-biqing-zhu