ChengF-Lab / autoCellLinks
☆16Updated 3 years ago
Alternatives and similar repositories for autoCell
Users that are interested in autoCell are comparing it to the libraries listed below
Sorting:
- ☆45Updated last month
- An unsupervised approach for the integrative analysis of single-cell multi-omics data☆30Updated 4 years ago
- Scripts for data and figure generation in SAVER paper☆17Updated 4 years ago
- cTPnet Package☆25Updated 3 years ago
- ☆12Updated 2 years ago
- ☆21Updated 3 years ago
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆26Updated 2 years ago
- Novel joint clustering method with scRNA-seq and CITE-seq data☆10Updated 4 years ago
- Enhancing spatial transcriptomics data by predicting the expression of unmeasured genes from a dissociated scRNA-seq data☆36Updated last year
- Additional code and analysis from the single-cell integration benchmarking project☆67Updated 2 years ago
- ACTIONet single-cell analysis framework☆42Updated last year
- A novel computational method for inferring cell-type-specific signaling networks using single-cell transcriptomics data for better charac…☆43Updated 3 weeks ago
- Deep learning model for single-cell inference of multi-omic profiles from a single input modality.☆43Updated 2 years ago
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆39Updated 3 years ago
- ☆44Updated 3 years ago
- ☆32Updated 5 months ago
- Reproducing result from the paper☆34Updated 4 years ago
- Imputation method for scRNA-seq based on low-rank approximation☆77Updated last year
- This repository contains all code used for the Human Lung Cell Atlas project.☆54Updated 2 years ago
- Unsupervised cell functional annotation for single-cell RNA-Seq☆22Updated 2 years ago
- ☆18Updated 4 years ago
- Deciphering driver regulators of cell fate decisions from single-cell RNA-seq data☆25Updated 10 months ago
- ☆13Updated 5 years ago
- scMEGA: Single-cell Multiomic Enhancer-based Gene regulAtory network inference☆40Updated 11 months ago
- ☆40Updated last week
- 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
- Simultaneous deep generative modeling and clustering of single cell genomic data☆32Updated 2 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆53Updated 3 years ago
- SoptSC for single cell data analysis: unsupervised inference of clustering, cell lineage, pseudotime and cell-cell communication network …☆22Updated 4 years ago
- Generative adversarial networks for single-cell RNA-seq imputation☆39Updated 5 years ago