scCATCH
Cell annotator
Automated tool for annotating cell types from single-cell RNA sequencing data based on marker genes
Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
219 stars
5 watching
38 forks
Language: R
last commit: almost 2 years ago
Linked from 1 awesome list
cell-markerscluster-annotationmarker-genesrna-seqsequencingseuratsingle-celltranscriptometranscriptomics
Related projects:
Repository | Description | Stars |
---|---|---|
| A tool for accurately annotating cell types in single-cell RNA sequencing data using deep learning | 100 |
| Automated method for identifying putative cell types from single-cell RNA-seq data using clustering and machine learning | 94 |
| A tool to identify cell-specific markers from single-cell RNA sequencing data by filtering out genes with unimodal distributions and selecting synergistically expressed gene pairs. | 15 |
| Analyzes single-cell RNA-seq data to detect allele-specific copy number variations and infer lineage relationships in cancer cells | 171 |
| Automated assignment of cell types in single-cell RNA-seq data based on marker genes and patient/batch effects | 197 |
| An R package that facilitates analysis of single-cell RNA-seq data by identifying homogeneous groups of cells. | 110 |
| An R-based web application for guided single-cell RNA-seq data analysis and clustering | 33 |
| A tool for clustering cells from single cell RNA-Seq experiments | 121 |
| An R package that infers cell-cell communication and ligand-receptor-target networks from spatially resolved transcriptomic data | 61 |
| Automated cell filtering tool for single-cell RNA sequencing data analysis | 24 |
| Probabilistic analysis tools for single-cell omics data | 1,270 |
| An educational resource teaching computational analysis of single-cell RNA-seq data using R and Bioconductor tools | 125 |
| Analyzes single-cell multi-omics data from various modalities like RNA-seq and ATAC-seq | 16 |
| Provides tools and methods for analyzing single-cell RNA sequencing data using statistical models | 228 |
| Analyzing and comparing single-cell RNA-seq data across multiple conditions to infer cell trajectories and detect differential expression. | 25 |