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Detect, log, and remove outlier counts. This function removes any normalized regions counts that are more than n_sd standard deviations (default = 2) higher than their cohort mean.

find_outlier_counts.Rd

Detect, log, and remove outlier counts. This function removes any normalized regions counts that are more than n_sd standard deviations (default = 2) higher than their cohort mean.

Usage

find_outlier_counts(
  e,
  by = c("group", "sex"),
  n_sd = 2,
  remove = FALSE,
  log = TRUE
)

Arguments

e

experiment object

by

(str, default = c("group", "sex")) The mice attributes used to group the datasets into comparison groups.

n_sd

(int, default = 2). Number of standards deviations above and below which categorizes outliers.

remove

(bool, default = FALSE) Remove all outlier rows from the combined normalized counts dataframe in the experiment object.

log

(bool, default = TRUE) Save the logged outlier regions into a csv file in the output folder.

Value

e experiment object. Outlier counts in the experiment object are removed if remove = TRUE.

Examples

e <- find_outlier_counts(e, by = c("group","sex"), n_sd = 2, remove = FALSE, log = TRUE)
#> Error in find_outlier_counts(e, by = c("group", "sex"), n_sd = 2, remove = FALSE,     log = TRUE): object 'e' not found