Demonstration dataset for MS.test.clust

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)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MSeasy)
Loading required package: amap
Loading required package: clValid
Loading required package: cluster
Loading required package: fpc
Loading required package: mzR
Loading required package: Rcpp
Loading required package: xcms
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: ProtGenerics
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'xcms'

The following objects are masked from 'package:Biobase':

    phenoData, phenoData<-

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MSeasy/Data_testclust.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Data_testclust
> ### Title: Demonstration dataset for MS.test.clust
> ### Aliases: Data_testclust
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(Data_testclust)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>