FindVariableFeatures | R Documentation |
Identifies features that are outliers on a 'mean variability plot'.
FindVariableFeatures(object, ...)
## S3 method for class 'V3Matrix'
FindVariableFeatures(
object,
selection.method = "vst",
loess.span = 0.3,
clip.max = "auto",
mean.function = FastExpMean,
dispersion.function = FastLogVMR,
num.bin = 20,
binning.method = "equal_width",
verbose = TRUE,
...
)
## S3 method for class 'Assay'
FindVariableFeatures(
object,
selection.method = "vst",
loess.span = 0.3,
clip.max = "auto",
mean.function = FastExpMean,
dispersion.function = FastLogVMR,
num.bin = 20,
binning.method = "equal_width",
nfeatures = 2000,
mean.cutoff = c(0.1, 8),
dispersion.cutoff = c(1, Inf),
verbose = TRUE,
...
)
## S3 method for class 'SCTAssay'
FindVariableFeatures(object, nfeatures = 2000, ...)
## S3 method for class 'Seurat'
FindVariableFeatures(
object,
assay = NULL,
selection.method = "vst",
loess.span = 0.3,
clip.max = "auto",
mean.function = FastExpMean,
dispersion.function = FastLogVMR,
num.bin = 20,
binning.method = "equal_width",
nfeatures = 2000,
mean.cutoff = c(0.1, 8),
dispersion.cutoff = c(1, Inf),
verbose = TRUE,
...
)
object |
An object |
... |
Arguments passed to other methods |
selection.method |
How to choose top variable features. Choose one of :
|
loess.span |
(vst method) Loess span parameter used when fitting the variance-mean relationship |
clip.max |
(vst method) After standardization values larger than clip.max will be set to clip.max; default is 'auto' which sets this value to the square root of the number of cells |
mean.function |
Function to compute x-axis value (average expression). Default is to take the mean of the detected (i.e. non-zero) values |
dispersion.function |
Function to compute y-axis value (dispersion). Default is to take the standard deviation of all values |
num.bin |
Total number of bins to use in the scaled analysis (default is 20) |
binning.method |
Specifies how the bins should be computed. Available methods are:
|
verbose |
show progress bar for calculations |
nfeatures |
Number of features to select as top variable features;
only used when |
mean.cutoff |
A two-length numeric vector with low- and high-cutoffs for feature means |
dispersion.cutoff |
A two-length numeric vector with low- and high-cutoffs for feature dispersions |
assay |
Assay to use |
For the mean.var.plot method: Exact parameter settings may vary empirically from dataset to dataset, and based on visual inspection of the plot. Setting the y.cutoff parameter to 2 identifies features that are more than two standard deviations away from the average dispersion within a bin. The default X-axis function is the mean expression level, and for Y-axis it is the log(Variance/mean). All mean/variance calculations are not performed in log-space, but the results are reported in log-space - see relevant functions for exact details.
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