MouseRNAseqData {SingleR} | R Documentation

## 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"))

### 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.

### 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()

[Package SingleR version 1.2.4 Index]