PerturbVI
PerturbVI infers latent gene programs and their perturbation effects from single-cell Perturb-seq data.
[!NOTE] For the preprint, please see:
PerturbVI: A Scalable Latent Factor Model to Infer Genetic Regulatory Modules through CRISPR Perturbation Data.
doi.org/10.0000/perturbvi
[!IMPORTANT] To reproduce the analyses:
https://github.com/mancusolab/perturbvi_analysis
Installation
uv pip install perturbvi
Quick start
Prepare an H5AD file with transformed expression in adata.X and a binary,
named perturbation DataFrame in adata.obsm["G"].
from pathlib import Path
from perturbvi import fit_screen, load_screen, save_results
result_dir = Path("results/my_screen")
screen = load_screen("data/screen.h5ad")
fit = fit_screen(
screen,
z_dim=20,
l_dim=1000,
init="pca"
)
save_results(fit, result_dir)
This saves the fitted model and labeled result CSVs in result_dir.
See the tutorials for plotting and enrichment.
Tutorials
- LUHMES Analysis with PerturbVI: fitting, factor and gene effects, and neuronal GO enrichment.
- Replogle Analysis with PerturbVI: fitting and interpretation (TBD).
- Using PerturbVI with Your Data: CSV and AnnData inputs, controls, covariates, and fitting.
- API: function arguments, result matrices, and CLI.
Support
Please report bugs or feature requests in the issue tracker. For questions or comments, contact Abdullah Al Nahid (alnahid@usc.edu) or Nicholas Mancuso (nmancuso@usc.edu).
Other Software
Other software developed by the Mancuso Lab:
- SuShiE: a Bayesian fine-mapping framework for molecular QTL data across multiple ancestries.
- jaxQTL: scalable, count-based large-scale eQTL mapping.
- MA-FOCUS: a Bayesian fine-mapping framework using TWAS statistics across multiple ancestries to identify causal genes for complex traits.
- SuSiE-PCA: scalable Bayesian variable selection for sparse principal component analysis.
- twas_sim: simulation of TWAS statistics.
- traceax: stochastic trace estimation for linear operators.
- FactorGo: scalable variational factor analysis for learning pleiotropic factors from GWAS summary statistics.
- HAMSTA: estimation of heritability explained by local ancestry data from admixture mapping summary statistics.
PerturbVI is distributed under the terms of the MIT license.
Metadata
Release files for perturbvi 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| perturbvi-0.3.1.tar.gz | 40.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| perturbvi-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 88.7 kB
Release files / perturbvi-0.3.1.tar.gz
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Release files / perturbvi-0.3.1-py3-none-any.whl
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