Imports mitochondrial gene sets and stores it in the metadata of the SingleCellExperiment object. These gene sets can be used in downstream quality control and analysis functions in singleCellTK.
importMitoGeneSet(
inSCE,
reference = "human",
id = "ensembl",
by = "rownames",
collectionName = "mito",
noMatchError = TRUE
)Input SingleCellExperiment object.
Character. Species available are "human" and "mouse".
Types of gene id. Now it supports "symbol", "entrez", "ensembl" and "ensemblTranscriptID".
Character. Describes the location within inSCE where the gene
identifiers in the mitochondrial gene sets should be mapped.
If set to "rownames" then the features will
be searched for among rownames(inSCE). This can also be
set to one of the column names of rowData(inSCE) in which case the
gene identifies will be mapped to that column in the rowData
of inSCE. See featureIndex for more information.
Default "rownames".
Character. Name of collection to add gene sets to.
If this collection already exists in inSCE, then these gene sets will
be added to that collection. Any gene sets within the collection with the
same name will be overwritten. Default "mito".
Boolean. Show an error if a collection does not have
any matching features. Default TRUE.
A SingleCellExperiment object
with gene set from collectionName output stored to the
metadata slot.
The gene identifiers of mitochondrial genes will be loaded with
"data(AllMito)". Currently, it supports human and mouse references.
Also, it supports entrez ID, gene symbol, ensemble ID and ensemble transcript ID.
They will be mapped to the IDs in inSCE using the by parameter and
stored in a GeneSetCollection object from package
GSEABase. This object is stored in
metadata(inSCE)$sctk$genesets, which can be accessed in downstream
analysis functions such as runCellQC.
importGeneSetsFromList for importing from lists, importGeneSetsFromGMT for importing from GMT files, and GeneSetCollection objects.
data(scExample)
sce <- importMitoGeneSet(inSCE = sce,
reference = "human",
id = "ensembl",
collectionName = "human_mito",
by = "rownames")