vandijklab / scGAT
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>
☆16Updated 4 years ago
Alternatives and similar repositories for scGAT:
Users that are interested in scGAT are comparing it to the libraries listed below
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 3 years ago
- Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks☆19Updated 8 months ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆49Updated 3 years ago
- A deep-learning framework for multi-omics integration☆25Updated last year
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆24Updated last year
- Python Implementation of SIMLR for single-cell visualization and analysis☆23Updated 2 years ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 3 years ago
- Multi-omics integration method using AE and GCN☆34Updated last year
- Cell clustering for spatial transcriptomics data with graph neural network☆59Updated last year
- ☆8Updated 5 years ago
- The source code and results for different methods on annotating external testing datsets of human and mouse.☆12Updated 3 years ago
- VEGA: VAE Enhanced by Gene Annotations☆15Updated 2 years ago
- MOLI: Multi-Omics Late Integration with deep neural networks for drug response prediction☆55Updated 4 years ago
- covolutional neural network based coexpression analysis☆76Updated 4 years ago
- ☆16Updated 4 years ago
- Deep soft K-means clustering with self-training for single cell RNA sequence data☆24Updated 4 years ago
- ☆15Updated 4 years ago
- Single cell joint embedding and modality prediction with autoencoder☆9Updated 2 years ago
- Generative adversarial networks for single-cell RNA-seq imputation☆39Updated 4 years ago
- ☆42Updated 3 months ago
- Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis☆54Updated 3 years ago
- DCAP:Integrating multi-omics data with deep learning for predicting cancer prognosis☆21Updated 4 years ago
- scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics☆41Updated 2 years ago
- ☆65Updated last year
- Multi-task deep learning framework for multi-omics data analysis☆41Updated 2 years ago
- ☆28Updated 3 years ago
- scDCC: Single Cell Deep Constrained Clustering☆41Updated 8 months ago
- ☆18Updated 3 years ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆48Updated last month
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆37Updated 2 years ago