Maldi.train.small: Maldi.train.small: MALDI-TOF MS on Cow Milk

In thoree/stat340: Data and functions for BIAS at NMBU

Maldi.train.small: MALDI-TOF MS on Cow Milk

Description

This data is from an article in Chemometrics and Intelligent Laboratory Systems about quantitative whole spectrum analysis with MALDI-TOF MS on skimmed milk from cow, goat and ewe. MALDI-TOF is a mass spectrometry technique used for identifying ionizable components, such as proteins and peptides in samples. This is the data from MALDI-TOF mass spectrometry (MS) on cow milk for four replicates of 45 different milk mixtures.

Usage

Maldi.train.small

Format

A data frame with 180 observations (rows) and 1031 variables (columns).

	Columns	Data type	Description	Values
[,1]	Percent_milk	numeric	The percentage of cow milk	(0 - 0.9631)
[,2:1031]	MSdata1...MSdata6175	numeric	MS data for the milk samples	(-0.6186222 - 6.668699)

The variables with mass spectrometry data, Maldi.train[, 2:1031], are a quantification of molecule “size” and “charge” in a sample. For simplicity we may say that the size of molecules increases from variable 2 to variable 1031.The measurements are then the amounts of molecules of different sizes. The method is used to separate proteins, peptides and other ionizable compunds.

Details

The Maldi data was split into training data, which can be used to fit a model, and test data that can be used to evaluate the model.

This data set is a subset of the Maldi.train data (selected columns).

References

Liland, K. H., Mevik, B., Rukke, E., Almøy, T., Skaugen, M., Isaksson, T. (2009) Quantitative whole spectrum analysis with MALDI-TOF MS, Part I: Measurement optimisation. Chemometrics and Intelligent Laboratory Systems, 96, 210 - 218.

See Also

Maldi.test.small, Maldi.test and Maldi.train

Examples

# Dimensions of the object
dim(Maldi.train.small)

# Plot one of the spectra
plot(Maldi.train.small[, 2], type = "l")

# Plot several spectra
matplot(Maldi.train.small[, 2:6], type = "l", lty = 1)

thoree/stat340 documentation built on June 30, 2024, 4:04 p.m.