Metadata-Version: 2.1
Name: antpack
Version: 0.1.5.2
Summary: A Python package for processing, manipulating and making inferences about antibody sequence data
Home-page: UNKNOWN
License: UNKNOWN
Platform: UNKNOWN
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE

# AntPack

AntPack is a toolkit for data processing, statistical inference and
machine learning for antibody sequences. It is currently in
active development -- more updates soon! For installation and how to
use, see [the docs](https://antpack.readthedocs.io/en/latest/index.html).


### Antibody numbering

Numbering antibody sequences is an important precursor for many statistical inference /
machine learning applications. AntPack is orders of magnitude faster for numbering
antibody sequences than existing tools in the literature (e.g. ANARCI, AbRSA),
while providing >= reliability.


### Humanness and developability

Minimizing the risk of immunogenicity is important for selecting clinical
candidates. In AntPack v0.1.0, we introduce a simple, fully interpretable
generative model for human heavy and light chains that outperforms all
comparators in the literature on a large held-out test set for distinguishing
human sequences from those of other species. This scoring tool can be used
to score sequences for humanness, suggest modifications to make them more
human, identify liabilities, and generate highly human sequences that contain
selected motifs.

### Citing this work

If using AntPack in research intended for publication, please cite:

[Jonathan Parkinson and Wei Wang. 2024. For antibody sequence generative modeling,
mixture models may be all you need. bioRxiv:
https://doi.org/10.1101/2024.01.27.577555](https://www.biorxiv.org/content/10.1101/2024.01.27.577555v1)


