% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/doc-data.R
\docType{data}
\name{Exp1_R2_pept}
\alias{Exp1_R2_pept}
\title{Exp1_R2_pept dataset}
\format{
An object of class \code{MSnSet} related to peptide
quantification. It contains 6 samples divided into two conditions
(10fmol and 5fmol) and 14048 peptides.

The data frame exprs(Exp1_R2_pept) contains six columns that are the 
quantitation of peptides for the six replicates. 

The data frame fData(Exp1_R2_pept) contains the meta data about the peptides.

The data frame pData(Exp1_R2_pept) contains the experimental design and 
gives few informations about the samples.
}
\usage{
data(Exp1_R2_pept)
}
\value{
An object of class \code{MSnSet} related to peptides
quantification.
}
\description{
This dataset is the final outcome of a quantitative mass 
spectrometry-based proteomic analysis of two samples containing different 
concentrations of 48 human proteins (UPS1 standard from Sigma-Aldrich) 
within a constant yeast background (see Giai Gianetto et al. (2016) for 
details). It contains the abundance values of the different human and 
yeast peptides identified and quantified in these two conditions. The two 
conditions represent the measured abundances of peptides when respectively 
5 fmol and 10 fmol of UPS1 human proteins were mixed with the yeast extract 
before mass spectrometry analyses. This results in a concentration ratio 
of 2.Three technical replicates were acquired for each condition.

The dataset is either available as a CSV file (see 
inst/extdata/Exp1_R2_pept.txt), or as a \code{MSnSet} structure 
(Exp1_R2_pept). In the latter case, the quantitative data are those of the 
raw intensities.
}
\references{
Cox J., Hein M.Y., Luber C.A., Paron I., Nagaraj N., Mann M. 
Accurate proteome-wide label-free quantification by delayed normalization 
and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics. 
2014 Sep, 13(9):2513-26.

Giai Gianetto, Q., Combes, F., Ramus, C., Bruley, C., Coute, Y., 
Burger, T. (2016). Calibration plot for proteomics: A graphical tool to 
visually check the assumptions underlying FDR control in quantitative 
experiments. Proteomics, 16(1), 29-32.
}
\keyword{data}
\keyword{datasets}
