Exp1_R25_prot: Exp1_R25_prot dataset

In samWieczorek/DAPARdata: Data accompanying the DAPAR and Prostar packages

Exp1_R25_prot dataset

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 proteins identified and quantified in these two conditions. The two conditions represent the measured abundances of proteins when respectively 25 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 2.5. Three technical replicates were acquired for each condition.

The dataset is either available as a CSV file (see inst/extdata/Exp1_R25_prot.txt), or as a MSnSet structure (Exp1_R25_prot.MSnset). In the latter case, the quantitative data are those of the raw intensities.

Usage

data(Exp1_R25_prot)

Format

An object of class MSnSet related to proteins quantification. It contains 6 samples divided into two conditions (25 fmol and 10 fmol) and 2384 proteins.

The data frame exprs(Exp1_R25_prot) contains six columns that are the quantitation of proteins for the six replicates.

The data frame fData(Exp1_R25_prot) contains the meta data about the proteins.

The data frame pData(Exp1_R25_prot) contains the experimental design and gives few informations about the samples.

Value

An object of class MSnSet related to proteins quantification.

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.

samWieczorek/DAPARdata documentation built on April 22, 2022, 9:35 p.m.