lab-conrad / resVAELinks
resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially using single-cell RNA sequencing. In principle it can be used with any hierarchically structured data though, so feel free to play around with it.
☆12Updated 2 years ago
Alternatives and similar repositories for resVAE
Users that are interested in resVAE are comparing it to the libraries listed below
Sorting:
- ☆56Updated last year
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆52Updated 3 years ago
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆26Updated 2 years ago
- BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.☆31Updated 5 years ago
- Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis☆54Updated 2 months ago
- Learning meaningful representations of genes☆19Updated last month
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆39Updated 3 years ago
- Matilda is a multi-task framework for learning from single-cell multimodal omics data. Matilda leverages the information from the multi-m…☆21Updated 2 months ago
- Unsupervised cell functional annotation for single-cell RNA-Seq☆22Updated 2 years ago
- ☆45Updated last month
- ☆32Updated 4 months ago
- Deep Generative Modeling of RNA Velocity☆35Updated 3 months ago
- ☆30Updated 3 years ago
- Code for reproducing "Exploring genetic interaction manifolds constructed from rich single-cell phenotypes"☆58Updated 5 years ago
- SIMBA: SIngle-cell eMBedding Along with features☆63Updated 10 months ago
- ACTIONet single-cell analysis framework☆42Updated 11 months ago
- ☆18Updated 4 years ago
- ☆16Updated last month
- Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)☆19Updated 2 months ago
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 2 years ago
- Simultaneous deep generative modeling and clustering of single cell genomic data☆32Updated 2 years ago
- MOJITOO: a fast and universal method for integration of multimodal single cell data☆11Updated 10 months ago
- ☆16Updated 2 years ago
- ☆16Updated 3 years ago
- Deep learning model for single-cell inference of multi-omic profiles from a single input modality.☆43Updated 2 years ago
- Regulatory networks with Direct Information in python☆40Updated 2 years ago
- Semi-supervised adversarial neural networks for classification of single cell transcriptomics data☆75Updated 7 months ago
- ☆50Updated 5 months ago
- Enhancing spatial transcriptomics data by predicting the expression of unmeasured genes from a dissociated scRNA-seq data☆36Updated last year