BayesSpace
Gene clustering tool
A Bayesian model for clustering and enhancing spatial gene expression data
Bayesian model for clustering and enhancing the resolution of spatial gene expression experiments.
114 stars
3 watching
22 forks
Language: R
last commit: about 1 year ago Related projects:
| Repository | Description | Stars |
|---|---|---|
| | A software tool used to perform Bayesian consensus clustering of data. | 19 |
| | An open-source software tool for applying consensus clustering to multi-omic data for disease subtyping | 5 |
| | An R application for conducting Bayesian analyses of genomic models using a user-friendly interface. | 5 |
| | A tool to automatically identify co-expressed genes across multiple single-cell RNA-seq datasets | 2 |
| | Tools and methods to analyze gene expression data in relation to spatial coordinates | 151 |
| | Software package for cell type identification and differential expression in spatial transcriptomics | 322 |
| | A Python library for Bayesian inference and multinomial mixture modeling | 108 |
| | A software framework for learning spatial embeddings from high-dimensional transcriptomics data using an adaptive graph attention auto-encoder | 41 |
| | A Python package for aligning single-cell transcriptomic data with spatial gene expression data. | 261 |
| | A tool for clustering cells from single cell RNA-Seq experiments | 121 |
| | A software package that uses Bayesian inference to assign gene expression estimates from single-cell RNA-seq and DNA-seq data to specific cancer clones. | 32 |
| | An open-source software pipeline that uses Hidden-Markov-Models to identify genes in metagenomics data and provide reliable results | 4 |
| | A software framework for analyzing single-cell DNA methylation data using Bayesian methods | 14 |
| | An R package that uses Bayesian inference and hidden Markov models to detect genetic variations in single-cell RNA-seq data | 98 |
| | An application of machine learning to cluster similar data points from various sources | 0 |