MouseRNAseqData: Obtain mouse bulk expression data of sorted cell populations...

In LTLA/celldex: Index of Reference Cell Type Datasets

Obtain mouse bulk expression data of sorted cell populations (RNA-seq)

Description

Download and cache the normalized expression values of 358 bulk RNA-seq samples of sorted cell populations that can be found at GEO.

Usage

MouseRNAseqData(
  ensembl = FALSE,
  cell.ont = c("all", "nonna", "none"),
  legacy = FALSE
)

Arguments

ensembl	Logical scalar indicating whether to convert row names to Ensembl IDs. Genes without a mapping to a non-duplicated Ensembl ID are discarded.
cell.ont	String specifying whether Cell Ontology terms should be included in the colData. If "nonna", all samples without a valid term are discarded; if "all", all samples are returned with (possibly NA) terms; if "none", terms are not added.
legacy	Logical scalar indicating whether to pull data from ExperimentHub. By default, we use data from the gypsum backend.

Details

This dataset was contributed by the Benayoun Lab that identified, downloaded and processed data sets on GEO that corresponded to sorted cell types (Benayoun et al., 2019).

The dataset contains 358 mouse RNA-seq samples annotated to 18 main cell types ("label.main"):

• Adipocytes

• Astrocytes

• B cells

• Cardiomyocytes

• Dendritic cells

• Endothelial cells

• Epithelial cells

• Erythrocytes

• Fibroblasts

• Granulocytes

• Hepatocytes

• Macrophages

• Microglia

• Monocytes

• Neurons

• NK cells

• Oligodendrocytes

• T cells

These are split further into 28 subtypes ("label.fine"). The subtypes have also been mapped to the Cell Ontology ("label.ont", if cell.ont is not "none"), which can be used for further programmatic queries.

Value

A SummarizedExperiment object with a "logcounts" assay containing the log-normalized expression values, along with cell type labels in the colData.

Author(s)

Friederike Dündar

References

Benayoun B et al. (2019). Remodeling of epigenome and transcriptome landscapes with aging in mice reveals widespread induction of inflammatory responses. Genome Res. 29, 697-709.

Code at https://github.com/BenayounLaboratory/Mouse_Aging_Epigenomics_2018/tree/master/FigureS7_CIBERSORT/RNAseq_datasets_for_Deconvolution/2017-01-18

Examples

ref.se <- MouseRNAseqData()

LTLA/celldex documentation built on June 3, 2024, 4:53 p.m.