vandijklab / scGATLinks
Code to reproduce results in Ravindra NG* & Sehanobish A* et al. 2020, "Disease State Prediction From Single-Cell Data Using Graph Attention Networks" to appear in ACM Proceedings. <https://arxiv.org/abs/2002.07128>
☆17Updated 5 years ago
Alternatives and similar repositories for scGAT
Users that are interested in scGAT are comparing it to the libraries listed below
Sorting:
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- Python Implementation of SIMLR for single-cell visualization and analysis☆23Updated 3 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆50Updated 3 years ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 3 years ago
- DCAP:Integrating multi-omics data with deep learning for predicting cancer prognosis☆21Updated 4 years ago
- scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks☆149Updated last year
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 2 years ago
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆26Updated 2 years ago
- ☆30Updated 3 years ago
- ☆20Updated 4 years ago
- A deep-learning framework for multi-omics integration☆26Updated 2 years ago
- Generative adversarial networks for single-cell RNA-seq imputation☆39Updated 5 years ago
- Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks☆19Updated last year
- covolutional neural network based coexpression analysis☆79Updated 5 years ago
- Multi-task deep learning framework for multi-omics data analysis☆47Updated 3 years ago
- VEGA: VAE Enhanced by Gene Annotations☆16Updated 3 years ago
- Cell clustering for spatial transcriptomics data with graph neural network☆63Updated 2 years ago
- The source code and results for different methods on annotating external testing datsets of human and mouse.☆12Updated 4 years ago
- ☆67Updated last year
- Graph Neural Network model for survival analysis from multi-omics data☆13Updated 3 years ago
- P-NET, Biologically informed deep neural network for prostate cancer classification and discovery☆156Updated 3 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
- ☆9Updated 5 years ago
- ☆16Updated 4 years ago
- Python framework for single-cell RNA-seq clustering with special focus on transfer learning.☆18Updated 5 years ago
- An accurate and efficient deep learning method for single-cell RNA-seq data imputation☆89Updated 3 years ago
- Multi-omics biomarker discovery tool exploiting a gene-gene interaction network☆16Updated last year
- ☆42Updated 7 months ago
- Conditional out-of-distribution prediction☆63Updated last year
- End-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets.☆34Updated 4 years ago