README.md

In grisslab/scAnnotatR: Pretrained learning models for cell type prediction on single cell RNA-sequencing data

scAnnotatR

The scAnnotatR package automatically classifies cells in scRNA-seq datasets. It is simple to use with a clear infrastructure to easily add additional cell type classification models. scAnnotatR support both Seurat and SingleCellExperiment objects as input.

Installation

You can install the latest version directly from GitHub using the devtools package:

# install devtools if needed
if (!require(devtools)) {
  install.packages("devtools")
}

if (!require(scAnnotatR)) {
  install_github("grisslab/scAnnotatR")
}

Help

The complete usage is shown in the vignettes:

• Basic classification of cells
• Basic training of a new cell classification model
• Training of child-celltype models

For more questions / feedback please simply post an Issue.

Citation

If you used scAnnotatR in your research, we would be grateful if you could cite the following manuscript:

Nguyen, V., Griss, J. scAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data. BMC Bioinformatics 23, 44 (2022). https://doi.org/10.1186/s12859-022-04574-5

grisslab/scAnnotatR documentation built on March 20, 2023, 2:42 a.m.