The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.
☆150Aug 14, 2024Updated 2 years ago
Alternatives and similar repositories for cpa
Users that are interested in cpa are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆157Feb 6, 2025Updated last year
- GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations☆403Feb 1, 2025Updated last year
- Notebooks for CPA figures☆15Dec 9, 2022Updated 3 years ago
- GenePert: Leveraging GenePT Embeddings for Gene Perturbation Prediction☆21Oct 29, 2024Updated last year
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆187Feb 25, 2025Updated last year
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- ☆53Jun 16, 2025Updated last year
- Single-cell perturbation analysis☆337Updated this week
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell lev…☆186Sep 7, 2023Updated 2 years ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆66Jan 12, 2026Updated 7 months ago
- Single-cell perturbation effects prediction benchmark☆103May 6, 2026Updated 3 months ago
- State is a machine learning model that predicts cellular perturbation response across diverse contexts☆658Jul 24, 2026Updated last month
- ☆15Jul 8, 2022Updated 4 years ago
- Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)☆18Jun 15, 2025Updated last year
- ☆96Aug 10, 2026Updated 3 weeks ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- ☆72Jan 14, 2026Updated 7 months ago
- ☆40Apr 16, 2025Updated last year
- ☆92Jul 18, 2025Updated last year
- Single cell perturbation prediction☆355Dec 5, 2024Updated last year
- pytorch dataloaders for single-cell perturbation data☆51Jul 18, 2026Updated last month
- Modeling and predicting single-cell multi-gene perturbation responses with scLAMBDA☆27Mar 20, 2026Updated 5 months ago
- Comprehensive suite for evaluating perturbation prediction models☆155Jul 27, 2026Updated last month
- CellDrift: temporal perturbation effects for single cell data☆13Dec 3, 2022Updated 3 years ago
- Reference mapping for single-cell genomics☆407Jun 26, 2026Updated 2 months ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- ☆1,620Apr 29, 2026Updated 4 months ago
- R package that performs sparse factor analysis and differential gene expression discovery simultaneously on single-cell CRISPR screening …☆25Oct 3, 2023Updated 2 years ago
- Conditional out-of-distribution prediction☆63Aug 2, 2024Updated 2 years ago
- Code for reproducing "Exploring genetic interaction manifolds constructed from rich single-cell phenotypes"☆71Jun 6, 2020Updated 6 years ago
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆181Oct 31, 2024Updated last year
- PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturb…☆89Dec 13, 2024Updated last year
- Interpret perturbation responses from scRNA-seq perturbation experiments☆17Mar 4, 2025Updated last year
- Quantifying experimental perturbations at single cell resolution☆116Sep 27, 2024Updated last year
- Models and datasets for perturbational single-cell omics☆182Aug 19, 2022Updated 4 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Deep probabilistic analysis of single-cell and spatial omics data☆1,684Updated this week
- SEACells algorithm for Inference of transcriptional and epigenomic cellular states from single-cell genomics data☆196Aug 24, 2026Updated last week
- ☆18Apr 23, 2026Updated 4 months ago
- Package to preprocess ontologies and train OntoVAE models.☆16Jan 7, 2025Updated last year
- ☆101Aug 12, 2024Updated 2 years ago
- Perturbational analysis by causality-aware generative model for single-cell RNA-sequencing data☆23Dec 16, 2025Updated 8 months ago
- Pipeline to run scE2G☆61Updated this week