zhangxiaoyu11 / XOmiVAELinks
An interpretable deep learning model for cancer classification using high-dimensional omics data
☆16Updated 3 years ago
Alternatives and similar repositories for XOmiVAE
Users that are interested in XOmiVAE are comparing it to the libraries listed below
Sorting:
- scDCC: Single Cell Deep Constrained Clustering☆42Updated last year
- Python framework for single-cell RNA-seq clustering with special focus on transfer learning.☆18Updated 6 years ago
- The source code and results for different methods on annotating external testing datsets of human and mouse.☆12Updated 4 years ago
- Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis☆54Updated 6 months ago
- SemI-SUpervised generative Autoencoder models for single cell data☆18Updated 4 years ago
- Single-cell RNA-seq clustering and annotation☆13Updated 5 years ago
- ☆14Updated 4 years ago
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆25Updated 2 years ago
- Cell clustering for spatial transcriptomics data with graph neural network☆64Updated 2 years ago
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- ☆19Updated 4 years ago
- Deep joint-leaning single-cell multi-omics model☆15Updated 3 years ago
- ☆31Updated 2 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
- End-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets.☆34Updated 4 years ago
- a deep learning approach for integrative cancer subtyping of multi-omics data☆39Updated last year
- ☆16Updated 3 years ago
- Experimental evaluation and comparison of multi-omics data integration methods for cancer subtyping☆14Updated 4 years ago
- Deep soft K-means clustering with self-training for single cell RNA sequence data☆27Updated 5 years ago
- ☆15Updated last year
- scGMAI: a Gaussian mixture model for clustering single-cell RNA-seq data based on deep autoencoder☆15Updated 4 years ago
- Multi-task deep learning framework for multi-omics data analysis☆48Updated 3 years ago
- DCAP:Integrating multi-omics data with deep learning for predicting cancer prognosis☆21Updated 4 years ago
- ☆20Updated 4 years ago
- Spatial cellular architecture predicts prognosis in glioblastoma - Nature Communications☆25Updated 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
- ☆34Updated 7 months ago
- Code to reproduce results in Ravindra NG* & Sehanobish A* et al. 2020, "Disease State Prediction From Single-Cell Data Using Graph Attent…☆18Updated 5 years ago
- ☆19Updated 4 years ago
- scDeepCluster for Single Cell RNA-seq data☆103Updated last year