Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics
-
Updated
Jun 4, 2024 - HTML
Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics
Unbiased single-cell transcriptomic data cell type identification
Supervised cell type identification for scATAC-seq data
SCISSORS builds upon the Louvain graph-based clustering in Seurat by optimizing parameter selection when reclustering cell groups, with an eye towards identifying rare cell types.
The official implementation for "SANGO".
High precision, marker-based, hierarchical cell-type annotation tool for single-cell RNA-seq data
Unsupervised cell type identification for spatial transcriptomics
MarkerCount is a python3 cell-type identification toolkit for single-cell RNA-Seq experiments.
Deep Learning single-cell Identification and Annotation
Hierarchical and high-resolution cell-type identification for single-cell RNA-seq data based on ScType.
R package to assign an initial bone-related cell type
Add a description, image, and links to the cell-type-identification topic page so that developers can more easily learn about it.
To associate your repository with the cell-type-identification topic, visit your repo's landing page and select "manage topics."