davidbuterez / CellVGAELinks
An unsupervised scRNA-seq analysis workflow with graph attention networks
☆25Updated 2 years ago
Alternatives and similar repositories for CellVGAE
Users that are interested in CellVGAE are comparing it to the libraries listed below
Sorting:
- ☆16Updated 3 years ago
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆53Updated 3 years ago
- Simultaneous deep generative modeling and clustering of single cell genomic data☆32Updated 3 years ago
- ☆30Updated 4 years ago
- Unsupervised cell functional annotation for single-cell RNA-Seq☆22Updated 2 years ago
- The source code and results for different methods on annotating external testing datsets of human and mouse.☆12Updated 4 years ago
- ☆45Updated 5 months ago
- Generative adversarial networks for single-cell RNA-seq imputation☆39Updated 5 years ago
- Semi-supervised adversarial neural networks for classification of single cell transcriptomics data☆76Updated last year
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆39Updated 3 years ago
- ☆19Updated 4 years ago
- Regulatory networks with Direct Information in python☆40Updated 2 years ago
- Quantifying experimental perturbations at single cell resolution☆112Updated last year
- SIMBA: SIngle-cell eMBedding Along with features☆65Updated last year
- 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
- ☆19Updated 4 years ago
- netNMF-sc: A network regularization algorithm for dimensionality reduction and imputation of single-cell expression data☆23Updated 4 years ago
- Conditional out-of-distribution prediction☆61Updated last year
- ☆34Updated 8 months ago
- Simulate single-cell RNA-SEQ data using the Splatter statistical framework but implemented in python. In addition, simulate doublet cells…☆28Updated 4 years ago
- resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially usin…☆12Updated 2 years ago
- An accurate and efficient deep learning method for single-cell RNA-seq data imputation☆89Updated 3 years ago
- SemI-SUpervised generative Autoencoder models for single cell data☆18Updated 4 years ago
- spatial transcriptome, single cell☆73Updated 2 years ago
- Deep Generative Modeling of RNA Velocity☆35Updated 2 months ago
- ☆60Updated last year
- scDCC: Single Cell Deep Constrained Clustering☆43Updated last year
- Learning motif contributions to cell transitions using sequence features and graphs.☆28Updated last year
- scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics☆41Updated 3 years ago