sample.outliers: outlier features count for samples

In MRCIEU/metaboprep: Metabolomics data preparation and processing pipeline

outlier features count for samples

Description

This function takes a matrix of numeric data and counts the number of outlying features each sample has.

Usage

sample.outliers(wdata, nsd = 5)

Arguments

wdata	a metabolite data matrix with samples in row, metabolites in columns
nsd	the number of standard deviation from the mean outliers are identified at. The default value is 5.

Value

a data frame of outiler counts for each sample

Examples

d = sapply(1:5, function(x){ rnorm(50, 50, 15) })
sample.outliers(d, nsd = 2)

MRCIEU/metaboprep documentation built on Jan. 28, 2023, 7:29 p.m.