BlueprintEncodeData {SingleR} | R Documentation

## Obtain human bulk RNA-seq data from Blueprint and ENCODE

### Description

Download and cache the normalized expression values of 259 RNA-seq samples of pure stroma and immune cells as generated and supplied by Blueprint and ENCODE.

### Usage

    BlueprintEncodeData(rm.NA = c("rows", "cols", "both", "none"), ensembl = FALSE)

### Arguments

`rm.NA` | String specifying how missing values should be handled. `"rows"` will remove genes with at least one missing value, `"cols"` will remove samples with at least one missing value, `"both"` will remove any gene or sample with at least one missing value, and `"none"` will not perform any removal.
`ensembl` | Logical scalar indicating whether to convert row names to Ensembl IDs. Genes without a mapping to a non-duplicated Ensembl ID are discarded.

### Details

This function provides normalized expression values of 259 bulk RNA-seq samples generated by Blueprint and ENCODE from pure populations of stroma and immune cells (Martens and Stunnenberg, 2013; The ENCODE Consortium, 2012).

Blueprint Epigenomics contains 144 RNA-seq pure immune samples annotated to 28 cell types. ENCODE contains 115 RNA-seq pure stroma and immune samples annotated to 17 cell types. Altogether, this reference contains 259 samples with 43 cell types.

The samples were processed and normalized as described in Aran, Looney and Liu et al. (2019); i.e. the raw RNA-seq counts were downloaded from Blueprint and ENCODE in 2016 and normalized via edgeR (TPMs).

The data will be downloaded from ExperimentHub, returning a SummarizedExperiment object for further use.

### 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

The ENCODE Project Consortium (2012). An integrated encyclopedia of DNA elements in the human genome. Nature 489, pages 57–74.

Martens JHA and Stunnenberg HG (2013). BLUEPRINT: mapping human blood cell epigenomes. Haematologica 98, 1487–1489.

Aran D, Looney AP, Liu L et al. (2019). Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat. Immunol. 20, 163–172.

### Examples

    ref.se <- BlueprintEncodeData(rm.NA = "rows")

[Package SingleR version 1.0.6 Index]