theislab / cpa
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.
☆93Updated 5 months ago
Alternatives and similar repositories for cpa:
Users that are interested in cpa are comparing it to the libraries listed below
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆110Updated 5 months ago
- Models and datasets for perturbational single-cell omics☆149Updated 2 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆49Updated 3 years ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆105Updated this week
- ☆71Updated 5 months ago
- Codes for paper: Evaluating the Utilities of Large Language Models in Single-cell Data Analysis.☆62Updated 2 weeks ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆29Updated 2 months ago
- Additional code and analysis from the single-cell integration benchmarking project☆56Updated 2 years ago
- Single-Cell (Perturbation) Model Library☆35Updated last week
- Accelerated, Python-only, single-cell integration benchmarking metrics☆53Updated this week
- spatial transcriptome, single cell☆67Updated last year
- ☆17Updated 3 years ago
- ☆58Updated last year
- single cell foundation model for Gene network inference and more☆42Updated this week
- DIALOGUE is a dimensionality reduction method that uses cross-cell-type associations to identify multicellular programs (MCPs) and map th…☆108Updated last year
- Formalizing and benchmarking open problems in single-cell genomics☆56Updated last month
- Repository for Nicheformer: a foundation model for single-cell and spatial omics☆78Updated 3 weeks ago
- A unifying representation of single cell expression profiles that quantifies similarity between expression states and generalizes to repr…☆162Updated last month
- PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturb…☆36Updated last month
- Diffusion model for gene regulatory network inference.☆16Updated 8 months ago
- ☆113Updated 6 months ago
- Large language modeling applied to T-cell receptor (TCR) sequences.☆48Updated 2 years ago
- SIMBA: SIngle-cell eMBedding Along with features☆57Updated 3 months ago
- single cell foundation model for Gene network inference and more☆15Updated 4 months ago
- ☆27Updated last month
- Deep learning model for single-cell inference of multi-omic profiles from a single input modality.☆39Updated last year
- Multi-omic velocity inference☆108Updated 3 months ago
- scDesign3 generates realistic in silico data for multimodal single-cell and spatial omics☆88Updated 2 months ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆47Updated this week
- Reproducing the experiments of the paper "Deep generative modeling for single-cell transcriptomics"☆56Updated 6 years ago