welch-lab / MichiGAN
Learning disentangled representations of single-cell data for high-quality generation
☆15Updated 8 months ago
Related projects ⓘ
Alternatives and complementary repositories for MichiGAN
- ☆16Updated 4 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆48Updated 2 years ago
- ☆28Updated 2 years ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆22Updated 2 years ago
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆24Updated last year
- Conditional out-of-distribution prediction☆55Updated 3 months ago
- Framework for integrating heterogeneous modalities of data☆16Updated 2 years ago
- Single cell joint embedding and modality prediction with autoencoder☆9Updated 2 years ago
- This Python package will allow you to replicate the experiments from our research on applying Optimal Transport as a similarity metric in…☆37Updated last year
- ☆16Updated 3 years ago
- Simultaneous deep generative modeling and clustering of single cell genomic data☆29Updated 2 years ago
- Regulatory networks with Direct Information in python☆38Updated last year
- ☆56Updated last year
- Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks☆18Updated 5 months ago
- ☆19Updated last year
- resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially usin…☆12Updated last year
- Maximum mean discrepancy comparisons for single cell profiling experiments☆15Updated 2 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆88Updated 3 months ago
- A simulator for single-cell expression data guided by gene regulatory networks☆55Updated 6 months ago
- CellBox: Interpretable Machine Learning for Perturbation Biology☆54Updated last year
- Semi-supervised adversarial neural networks for classification of single cell transcriptomics data☆73Updated 11 months ago
- Code for reproducing "Exploring genetic interaction manifolds constructed from rich single-cell phenotypes"☆49Updated 4 years ago
- Archetypal Analysis network (AAnet)☆31Updated 3 weeks ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆29Updated this week
- ☆36Updated last year
- VEGA: VAE Enhanced by Gene Annotations☆14Updated 2 years ago
- Generative adversarial networks for single-cell RNA-seq imputation☆36Updated 4 years ago
- Code for Nature Scientific Reports 2020 paper: "Unsupervised generative and graph neural methods for modelling cell differentiation" by I…☆18Updated 4 years ago
- Quantifying experimental perturbations at single cell resolution☆105Updated last month