outlier.summary: feature summary plots

In MRCIEU/metaboprep: Metabolomics data preparation and processing pipeline

feature summary plots

Description

This function plots the distribution of and identifiy outliers for every metabolite (column) in a data frame.

Usage

outlier.summary(dtst, pdf_filename = "./feature_distributions.pdf", nsd = 5)

Arguments

dtst	numeric data frame
pdf_filename	name of the pdf out file
nsd	number of SD to consider as outliers, 5 is default

Value

print summary figures for each column of data in the data frame to a pdf file.

Examples

## define a covariance matrix
cmat = matrix(1, 4, 4 )
cmat[1,] = c(1, 0.8, 0.6, 0.2)
cmat[2,] = c(0.8, 1, 0.7, 0.5)
cmat[3,] = c(0.6, 0.7, 1, 0.6)
cmat[4,] = c(0.2, 0.5, 0.6,1)
## simulate some correlated data (multivariable random normal)
set.seed(1110)
d1 = MASS::mvrnorm(n = 250, mu = c(5, 45, 25, 15), Sigma = cmat )
set.seed(1010)
d2 = MASS::mvrnorm(n = 250, mu = c(5, 45, 25, 15), Sigma = cmat )
## simulate some random data
d3 = sapply(1:20, function(x){ rnorm(250, 40, 5) })
## define the data set
ex_data = cbind(d1,d2,d3)
rownames(ex_data) = paste0("ind", 1:nrow(ex_data))
colnames(ex_data) = paste0("var", 1:ncol(ex_data))
## run the function
outlier.summary(ex_data)

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