Data_testclust: Demonstration dataset for MS.test.clust

In MSeasy: Preprocessing of Gas Chromatography-Mass Spectrometry (GC-MS) data

Description

To test for the best unsupervised clustering method, a dataset where molecules are already identified is created. Each molecule is represented by several samples mass spectrum. Here, the dataset contains 10 molecules obtained in different samples (84 Lavandula GC-MS analyses). In the function MS.test.clust, different clustering methods are tested for their abilities to find the correct structure of the dataset. Three different cluster validity indices are calculated to evaluate the results: the matching coefficient, the silhouette width and the Dunn index (see MS.test.clust for details)

Usage

data(Data_testclust)

Format

A data frame with 10 molecules from 84 GC-MS analyses.

• header line the first row must contains the columns' names

• first column name of the molecule

• second column sample name

• third column retention time

• following columns mean relative mass spectrum of the molecule (the intensity of one mass fragment (m/z) per column; Mean mass spectrum calculated by averaging 5 percent of the mass spectra surrounding the apex; The intensity of each mass fragment is transformed to a relative percentage of the highest mass fragment per spectrum)

Examples

data(Data_testclust)

MSeasy documentation built on May 2, 2019, 10:02 a.m.