In grisslab/scAnnotatR.models: Pretrained models for scAnnotatR package

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Introduction

The scAnnotatR.models packages contains a set of pre-trained models to classify various (immune) cell types in human data to be used by the scAnnotatR package.

scAnnotatR is an R package for cell type prediction on single cell RNA-sequencing data. Currently, this package supports data in the forms of a Seurat object or a SingleCellExperiment object.

If you are interested in directly applying these models to your data, please refer to the vignettes of the scAnnotatR package.

Installation

The scAnnotatR.models package is a AnnotationHub package. Normally, it is automatically loaded by the scAnnotatR package.

To load the package manually into your R session, please use the Bioconductor AnnotationHub package:

# use the AnnotationHub to load the scAnnotatR.models package
eh <- AnnotationHub::AnnotationHub()

# load the stored models
query <- AnnotationHub::query(eh, "scAnnotatR.models")
models <- query[["AH95906"]]

Data Structure

The models object is a named list containing the cell type's name as key and the respective classifier as value:

# print the available cell types
names(models)

Each classifier is an instance of the scAnnotatR S4 class. For example:

models[['B cells']]

Included models

The scAnnotatR package comes with several pre-trained models to classify cell types.

# Load the scAnnotatR package to view the models
library(scAnnotatR)

The models are stored in the default_models object:

default_models <- load_models("default")
names(default_models)

The default_models object is named a list of classifiers. Each classifier is an instance of the scAnnotatR S4 class. For example:

default_models[['B cells']]

Please refer to the scAnnotatR package documentation for detailed information about how to use these classifiers.

Session Info

sessionInfo()

grisslab/scAnnotatR.models documentation built on Dec. 20, 2021, 1:43 p.m.