View source: R/BlueprintEncodeData.R
BlueprintEncodeData | R Documentation |
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.
BlueprintEncodeData(
rm.NA = c("rows", "cols", "both", "none"),
ensembl = FALSE,
cell.ont = c("all", "nonna", "none"),
legacy = FALSE
)
rm.NA |
String specifying how missing values should be handled.
|
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 |
legacy |
Logical scalar indicating whether to pull data from ExperimentHub. By default, we use data from the gypsum backend. |
This function provides normalized expression values for 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). 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).
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.
All together, this reference contains 259 samples with 43 cell types ("label.fine"
),
manually aggregated into 24 broad classes ("label.main"
).
The fine labels have also been mapped to the Cell Ontology ("label.ont"
,
if cell.ont
is not "none"
), which can be used for further programmatic
queries.
A SummarizedExperiment object with a "logcounts"
assay
containing the log-normalized expression values, along with cell type labels in the
colData
.
Friederike Dündar
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.
ref.se <- BlueprintEncodeData(rm.NA = "rows")
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