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 (placeholder DOI)
[!IMPORTANT] To reproduce the analyses in the preprint:
zenodo.org/records/0000000 (placeholder)
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")
data = load_screen(
"data/screen.h5ad",
)
fit = fit_screen(
data,
z_dim=12,
l_dim=100,
)
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.
Release files for perturbvi 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| perturbvi-0.3.0.tar.gz | 40.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| perturbvi-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 89.1 kB
Release files / perturbvi-0.3.0.tar.gz
| Download URL | perturbvi-0.3.0.tar.gz |
|---|---|
| Size | 40.8 kB |
| Tags | Source |
|
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Release files / perturbvi-0.3.0-py3-none-any.whl
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