mvtcr

Name	mvtcr JSON
Version	0.2.1.1 JSON
	download
home_page	https://github.com/SchubertLab/mvTCR
Summary	mvTCR: A multimodal generative model to learn a unified representation across TCR sequences and scRNAseq data for joint analysis of single-cell immune profiling data
upload_time	2024-08-06 16:22:21
maintainer	Felix Drost, Yang An, Irene Bonafonte Pardàs, Jan-Philipp Leusch
docs_url	None
author	Felix Drost, Yang An, Lisa M Dratva, Rik GH Lindeboom, Muzlifah Haniffa, Sarah A Teichmann, Fabian Theis, Mohammad Lotfollahi, Benjamin Schubert
requires_python	None
license	None
keywords
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # mvTCR

mvTCR is a multimodal generative model to learn a unified representation across across TCR sequences and scRNAseq data and datasets for joint analysis of single-cell immune profiling data.

- The publication can be found [here](https://www.nature.com/articles/s41467-024-49806-9) 
- GitHub can be found [here](https://github.com/SchubertLab/mvTCR)

### Installation

To install mvTCR follow these steps:
1. Create a [conda](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment) environment: <code>conda create -n mvTCR python=3.10</code>
2. Install mvTCR <code>pip install mvTCR</code>
3. Install [PyTorch](https://pytorch.org/get-started/locally/) e.g. v2.1.2 with the appropriate CUDA version

### Tutorial

Please have a look at our tutorial notebooks found [here](https://github.com/SchubertLab/mvTCR/tree/master/tutorials).

### Bugs and Errors

If you find any bugs or run into errors please report them to our [GitHub](https://github.com/SchubertLab/mvTCR/issues).


#### Reproducibility 

The [reproducibility GitHub](https://github.com/SchubertLab/mvTCR_reproducibility) features experiments and code used in the publication. If you want to reproduce them, please use mvTCR v0.1.3 together with PyTorch v1.8.0 .

            

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