Signac (version 1.6.0)

FindTopFeatures: Find most frequently observed features

Description

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.

Usage

FindTopFeatures(object, ...)
# S3 method for default
FindTopFeatures(object, assay = NULL, min.cutoff = "q5", verbose = TRUE, ...)
# S3 method for Assay
FindTopFeatures(object, assay = NULL, min.cutoff = "q5", verbose = TRUE, ...)
# S3 method for Seurat
FindTopFeatures(object, assay = NULL, min.cutoff = "q5", verbose = TRUE, ...)

Arguments

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

Value

Returns a Seurat object

Examples

# NOT RUN {
FindTopFeatures(object = atac_small[['peaks']][])
FindTopFeatures(object = atac_small[['peaks']])
FindTopFeatures(atac_small)
# }