runPerCellQC | R Documentation |
A wrapper function for addPerCellQC. Calculate general quality control metrics for each cell in the count matrix.
runPerCellQC(
inSCE,
useAssay = "counts",
mitoGeneLocation = "rownames",
mitoRef = c(NULL, "human", "mouse"),
mitoIDType = c("ensembl", "symbol", "entrez", "ensemblTranscriptID"),
mitoPrefix = "MT-",
mitoID = NULL,
collectionName = NULL,
geneSetList = NULL,
geneSetListLocation = "rownames",
geneSetCollection = NULL,
percent_top = c(50, 100, 200, 500),
use_altexps = FALSE,
flatten = TRUE,
detectionLimit = 0,
BPPARAM = BiocParallel::SerialParam()
)
inSCE |
A SingleCellExperiment object. |
useAssay |
A string specifying which assay in the SCE to use. Default
|
mitoGeneLocation |
Character. Describes the location within |
mitoRef |
Character. The species used to extract mitochondrial genes ID
from build-in mitochondrial geneset in SCTK. Available species options are
|
mitoIDType |
Character. Types of mitochondrial gene id. SCTK supports
|
mitoPrefix |
Character. The prefix used to get mitochondrial gene from
either |
mitoID |
Character. A vector of mitochondrial genes to be quantified. |
collectionName |
Character. Name of a |
geneSetList |
List of gene sets to be quantified. The genes in the
assays will be matched to the genes in the list based on
|
geneSetListLocation |
Character or numeric vector. If set to
|
geneSetCollection |
Class of |
percent_top |
An integer vector. Each element is treated as a number of
top genes to compute the percentage of library size occupied by the most
highly expressed genes in each cell. Default |
use_altexps |
Logical scalar indicating whether QC statistics should
be computed for alternative Experiments in |
flatten |
Logical scalar indicating whether the nested
DataFrame-class in the output should be flattened. Default
|
detectionLimit |
A numeric scalar specifying the lower detection limit
for expression. Default |
BPPARAM |
A BiocParallelParam object specifying whether the QC
calculations should be parallelized. Default
|
This function allows multiple ways to import mitochondrial genes and quantify
their expression in cells. mitoGeneLocation
is required for all
methods to point to the location within inSCE object that stores the
mitochondrial gene IDs or Symbols. The various ways mito genes can be
specified are:
A combination of mitoRef
and mitoIDType
parameters can be used to load pre-built mitochondrial gene sets stored
in the SCTK package. These parameters are used in the
importMitoGeneSet function.
The mitoPrefix
parameter can be used to search for features
matching a particular pattern. The default pattern is an "MT-"
at the beginning of the ID.
The mitoID
parameter can be used to directy supply a vector of
mitochondrial gene IDs or names. Only features that exactly match items
in this vector will be included in the mitochondrial gene set.
A SingleCellExperiment object with cell QC metrics added to the colData slot.
addPerCellQC
,
link{plotRunPerCellQCResults}
, runCellQC
data(scExample, package = "singleCellTK")
mito.ix = grep("^MT-", rowData(sce)$feature_name)
geneSet <- list("Mito"=rownames(sce)[mito.ix])
sce <- runPerCellQC(sce, geneSetList = geneSet)
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