txWang / BERMUDA
BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.
☆30Updated 5 years ago
Alternatives and similar repositories for BERMUDA:
Users that are interested in BERMUDA are comparing it to the libraries listed below
- cTPnet Package☆24Updated 2 years ago
- ☆16Updated 3 years ago
- An unsupervised approach for the integrative analysis of single-cell multi-omics data☆29Updated 4 years ago
- Imputation method for scRNA-seq based on low-rank approximation☆74Updated last year
- Semi-supervised adversarial neural networks for classification of single cell transcriptomics data☆74Updated 2 months ago
- ☆10Updated last year
- ☆28Updated 5 years ago
- Simultaneous deep generative modeling and clustering of single cell genomic data☆30Updated 2 years ago
- R package for transfer learning of single-cell RNA-seq denoising☆29Updated 2 years ago
- Code for further development of the mutual nearest neighbours batch correction method, as implemented in the batchelor package.☆22Updated 5 years ago
- A study to compare methods for clustering of scRNA-seq data☆42Updated 7 months ago
- scLearn：Learning for single cell assignment☆35Updated 3 months ago
- ☆57Updated last year
- Generative adversarial networks for single-cell RNA-seq imputation☆39Updated 4 years ago
- scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics☆41Updated 2 years ago
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆37Updated 2 years ago
- Code for the MNN manuscript figures☆51Updated 6 years ago
- ☆45Updated 2 years ago
- Enhancing spatial transcriptomics data by predicting the expression of unmeasured genes from a dissociated scRNA-seq data☆33Updated 8 months ago
- Deep learning model for single-cell inference of multi-omic profiles from a single input modality.☆40Updated last year
- Code for Universal Single-Cell Matching with Unpaired Feature Sets☆21Updated 3 years ago
- MAGIC - imputation and de-noising single-cell RNA seq data sets☆27Updated 5 years ago
- Reproducing all analyses and figures for the ASAP-seq paper☆29Updated 3 years ago
- netNMF-sc: A network regularization algorithm for dimensionality reduction and imputation of single-cell expression data☆22Updated 3 years ago
- Quasilinear data representations for single-cell omics data analysis☆42Updated last year
- Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets☆30Updated last year
- Novel joint clustering method with scRNA-seq and CITE-seq data☆9Updated 3 years ago
- ☆34Updated last week
- Matilda is a multi-task framework for learning from single-cell multimodal omics data. Matilda leverages the information from the multi-m…☆20Updated 3 months ago
- ☆46Updated 2 years ago