MetRef: Nuclear Magnetic Resonance Spectra of Urine Samples

In KODAMA: Knowledge Discovery by Accuracy Maximization

Nuclear Magnetic Resonance Spectra of Urine Samples

Description

The data belong to a cohort of 22 healthy donors (11 male and 11 female) where each provided about 40 urine samples over the time course of approximately 2 months, for a total of 873 samples. Each sample was analysed by Nuclear Magnetic Resonance Spectroscopy. Each spectrum was divided in 450 spectral bins.

Usage

data(MetRef)

Value

A list with the following elements:

data	Metabolomic data. A matrix with 873 rows and 450 columns.
gender	Gender index. A vector with 873 elements.
donor	Donor index. A vector with 873 elements.

References

Assfalg M, Bertini I, Colangiuli D, et al.
Evidence of different metabolic phenotypes in humans.
Proc Natl Acad Sci U S A 2008;105(5):1420-4. doi: 10.1073/pnas.0705685105. Link

Cacciatore S, Luchinat C, Tenori L
Knowledge discovery by accuracy maximization.
Proc Natl Acad Sci U S A 2014;111(14):5117-22. doi: 10.1073/pnas.1220873111. Link

Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA
KODAMA: an updated R package for knowledge discovery and data mining.
Bioinformatics 2017;33(4):621-623. doi: 10.1093/bioinformatics/btw705. Link

Examples

data(MetRef)
u=MetRef$data;
u=u[,-which(colSums(u)==0)]
u=normalization(u)$newXtrain
u=scaling(u)$newXtrain
class=as.numeric(as.factor(MetRef$gender))
cc= pca(u)$x
plot(cc,pch=21,bg=class)

class=as.numeric(as.factor(MetRef$donor))
plot(cc,pch=21,bg=rainbow(22)[class])

kk=KODAMA.matrix(u)
cc=KODAMA.visualization(kk,"t-SNE")
plot(cc,pch=21,bg=rainbow(22)[class])

KODAMA documentation built on Jan. 12, 2023, 5:08 p.m.