Metadata-Version: 2.4
Name: crisprbact
Version: 1.3.1
Summary: Tools to design and analyse CRISPRi experiments
Project-URL: Homepage, https://gitlab.pasteur.fr/dbikard/crisprbact
Author-email: David Bikard <david.bikard@pasteur.fr>, Remi Planel <rplanel@pasteur.fr>
License-Expression: GPL-3.0
License-File: LICENSE
Keywords: CRISPR,CRISPRi,bacteria,genomics,screen
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.10
Requires-Dist: biopython>=1.79
Requires-Dist: click<9,>=8.0
Requires-Dist: numpy<3,>=1.21
Requires-Dist: pandas>=1.3
Requires-Dist: tqdm>=4.40
Provides-Extra: mcp
Requires-Dist: mcp<2,>=1.0; extra == 'mcp'
Provides-Extra: viz
Requires-Dist: matplotlib>=3.5; extra == 'viz'
Description-Content-Type: text/markdown

# CRISPRbact

**Tools to design and analyse CRISPRi experiments in bacteria.**

CRISPRbact is a Python library and command-line tool for designing CRISPRi (CRISPR interference) experiments with the *Streptococcus pyogenes* dCas9 protein in bacteria.

## Features

- **On-target activity prediction** — predicts how effectively each guide RNA will block gene expression, using a linear model trained on ~92,000 guides in *E. coli*
- **Genome-wide library design** — designs optimized CRISPRi libraries for any bacterial genome, selecting the best guides per gene while avoiding off-targets and toxic seed sequences
- **Library mapping** — evaluates an existing guide library against a new genome to assess coverage and predict activity
- **Add-on library design** — supplements an existing library (e.g. a core-genome library) with strain-specific guides to achieve full gene coverage
- **Core-genome library design** — designs guide libraries targeting genes conserved across multiple strains, enabling cross-strain CRISPRi screens

## Installation

```console
pip install crisprbact
```

## Quick example

```python
from crisprbact import on_target_predict

guides = on_target_predict("ACCACTGGCGTGCGCGTTACTCATCAGATGCTGTTCAATACCGATCAGGTTATCGAAGTGTTTGTGATTGTTTGCCGCGCGCGTGGCGAAGGCCCGTGATGAAGGAAAAGTTTTGCGCTATGTTGGCAATATTGATGAAG")

for g in guides:
    print(g["guide"], round(g["pred"], 2))
```

## Documentation

Full documentation (guides, API reference, output formats): **https://dbikard.pages.pasteur.fr/crisprbact/**

## References

- Calvo-Villamañán, Wong Ng et al., "On-target activity predictions enable improved CRISPR–dCas9 screens in bacteria", *Nucleic Acids Research*, 2020, 48(11):e64 ([doi:10.1093/nar/gkaa294](https://doi.org/10.1093/nar/gkaa294))
- Rousset F et al., "The impact of genetic diversity on gene essentiality within the *Escherichia coli* species." *Nature Microbiology* 6, 301–312 (2021) ([doi:10.1038/s41564-020-00839-y](https://doi.org/10.1038/s41564-020-00839-y))
- Rostain et al., "Cas9 off-target bindings as a source of far-reaching transcriptional noise", *Nucleic Acids Research*, 2023 ([doi:10.1093/nar/gkad170](https://doi.org/10.1093/nar/gkad170))
