Learn R Programming

MSstats (version 2.4.0)

QuantData: Quantitative data after data pre-processing and quality control of MS runs

Description

This is an example of quantitative data after data pre-processing and quality control of MS runs (i.e., transformation, normalization, and filtering of the original intensities measurements) and can be obtained directly from dataProcess.

Usage

QuantData

Arguments

Format

data.frame

Details

The quantitative data after data pre-processing and quality control of MS runs not only contain the same variable from the raw data, but with addition variables for statistical model fitting and group comparison. For examples, Variable ABUNDANCE represents the final measurement, which could be normalized or not depending on the options you specified in dataProcess. Default option in dataProcess is with log2 transformation and normalization.

References

Ching-Yun Chang, Paola Picotti, Ruth Huttenhain, Viola Heinzelmann-Schwarz, Marko Jovanovic, Ruedi Aebersold, Olga Vitek. Protein significance analysis in selected reaction monitoring (SRM) measurements. Molecular & Cellular Proteomics, 11:M111.014662, 2012.

Examples

Run this code
QuantData<-dataProcess(RawData)

head(QuantData)

Run the code above in your browser using DataLab