zhangxiaoyu11 / OmiVAELinks
End-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets.
☆34Updated 4 years ago
Alternatives and similar repositories for OmiVAE
Users that are interested in OmiVAE are comparing it to the libraries listed below
Sorting:
- MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in…☆164Updated 4 years ago
- ☆16Updated 4 years ago
- Multi-task deep learning framework for multi-omics data analysis☆46Updated 3 years ago
- An interpretable deep learning model for cancer classification using high-dimensional omics data☆15Updated 3 years ago
- scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks☆146Updated 11 months ago
- scDCC: Single Cell Deep Constrained Clustering☆40Updated last year
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- scDeepCluster for Single Cell RNA-seq data☆101Updated last year
- ☆42Updated 7 months ago
- Experimental evaluation and comparison of multi-omics data integration methods for cancer subtyping☆14Updated 3 years ago
- Python Implementation of SIMLR for single-cell visualization and analysis☆23Updated 2 years ago
- ☆76Updated 3 years ago
- Cell clustering for spatial transcriptomics data with graph neural network☆63Updated 2 years ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 3 years ago
- P-NET, Biologically informed deep neural network for prostate cancer classification and discovery☆156Updated 3 years ago
- ☆9Updated 5 years ago
- Deep soft K-means clustering with self-training for single cell RNA sequence data☆24Updated 4 years ago
- Identify spatial domain☆77Updated last month
- Code to reproduce results in Ravindra NG* & Sehanobish A* et al. 2020, "Disease State Prediction From Single-Cell Data Using Graph Attent…☆17Updated 5 years ago
- ☆14Updated last year
- HiGCN: a hierarchical graph convolution network for representation learning of gene expression data☆12Updated 4 years ago
- a unified single-cell data integration framework by optimal transport☆35Updated 9 months ago
- An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.☆152Updated 3 years ago
- Similarity network fusion in Python☆83Updated 5 years ago
- CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis☆33Updated 2 years ago
- Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis☆54Updated last month
- Code for Nature Scientific Reports 2020 paper: "Unsupervised generative and graph neural methods for modelling cell differentiation" by I…☆18Updated 4 years ago
- Deep-Learning framework for multi-omic and survival data integration☆82Updated last year
- single-cell graph autoencoder☆22Updated 3 years ago
- A deep-learning framework for multi-omics integration☆26Updated 2 years ago