sample.sum.stats: summary statistics for samples

In MRCIEU/metaboprep: Metabolomics data preparation and processing pipeline

summary statistics for samples

Description

This function estimates summary statistics for samples in a matrix of numeric features. This includes missingness, total peak area, and a count of the number of outlying features for a sample.

Usage

sample.sum.stats(wdata, feature_names_2_exclude = NA, outlier_udist = 5)

Arguments

wdata	the metabolite data matrix. samples in row, metabolites in columns
feature_names_2_exclude	a vector of feature|column names to exclude from missingness estimates
outlier_udist	the interquartile range unit distance from the median to call a sample an outlier at a feature.

Value

a data frame of summary statistics

Examples

## simulate some data
set.seed(1110)
ex_data = sapply(1:5, function(x){ rnorm(10, 40, 5) })
rownames(ex_data) = paste0("ind", 1:nrow(ex_data))
colnames(ex_data) = paste0("var", 1:ncol(ex_data))
## add some missingness to the data
ex_data[ sample(1:50, 10) ] = NA
## run estimate sample summary statistics
sample.sum.stats(ex_data)

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