Find most frequently observed features
Find top features for a given assay based on total number of counts for the
feature. Can specify a minimum cell count, or a lower percentile
bound to determine the set of variable features. Running this function will
store the total counts and percentile rank for each feature in the feature
metadata for the assay. To only compute the feature metadata, without
changing the variable features for the assay, set min.cutoff=NA.
FindTopFeatures(object, ...) ## Default S3 method: FindTopFeatures(object, assay = NULL, min.cutoff = "q5", verbose = TRUE, ...) ## S3 method for class 'Assay' FindTopFeatures(object, assay = NULL, min.cutoff = "q5", verbose = TRUE, ...) ## S3 method for class 'Seurat' FindTopFeatures(object, assay = NULL, min.cutoff = "q5", verbose = TRUE, ...)
object |
A Seurat object |
... |
Arguments passed to other methods |
assay |
Name of assay to use |
min.cutoff |
Cutoff for feature to be included in the VariableFeatures for the object. This can be a percentile specified as 'q' followed by the minimum percentile, for example 'q5' to set the top 95% most common features as the VariableFeatures for the object. Alternatively, this can be an integer specifying the minimum number of cells containing the feature for the feature to be included in the set of VariableFeatures. For example, setting to 10 will include features in >10 cells in the set of VariableFeatures. If NULL, include all features in VariableFeatures. If NA, VariableFeatures will not be altered, and only the feature metadata will be updated with the total counts and percentile rank for each feature. |
verbose |
Display messages |
Returns a Seurat object
FindTopFeatures(object = atac_small[['peaks']][]) FindTopFeatures(object = atac_small[['peaks']]) FindTopFeatures(atac_small)
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