Apples: Metabolomics data on spiked apples

In RankProd: Rank Product method for identifying differentially expressed genes with application in meta-analysis

Description

A dataset of LC-MS features, obtained from twenty apples. The last ten apples are spiked with known compounds. This set provides a test case for biomarker selection methods: the task is to retrive the true biomarker variables. The raw LC-MS data hava been converted to CDF format and processed with XCMS to obtain the basepeaks.

Usage

data(Apples)

Value

The format is a list of four elements:

mz	the m/z values of the features (rounded)
rt	the retention times of the features
apples.data	a matrix containing the intensities in the individual samples
apples.data.vsn	a matrix containing the intesities after variance stabilization and normalization performed with the vsn package
Biom	the indices of the "true" biomarkers
apples.cl	numeric vector encoding which samples are part of the spiked class (code 1) and which ones are controls (code 0)

Author(s)

Francesco Del Carratore

References

P. Franceschi, D. Masuero, U. Vrhovsek, F. Mattivi and R. Wehrens: A benchmark spike-in data set for biomarker identification in metabolomics. J. Chemom. 26, 16-24 (2012)

R. Wehrens, P. Franceschi, U. Vrhovsek and F. Mattivi. Stability-based biomarker selection. Analytica Chimica Acta (2011), 705, 15-23. http://dx.doi.org/10.1016/j.aca.2011.01.039

Examples

data(Apples)
## show features identified in all apples
plot(rt, mz,
     xlab = "Retention time (s)", ylab = "m/z",
     main = "Spiked apples - subset")

Example output

Loading required package: Rmpfr
Loading required package: gmp

Attaching package: 'gmp'

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

    %*%, apply, crossprod, matrix, tcrossprod

C code of R package 'Rmpfr': GMP using 64 bits per limb


Attaching package: 'Rmpfr'

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

    dbinom, dnorm, dpois, pnorm

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

    cbind, pmax, pmin, rbind

RankProd documentation built on Nov. 8, 2020, 8 p.m.