transformMSstatsToMSnSet: Transformation input format for MSstats to MSnSet class

In lindsaypino/MSstats-patch: Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments

Description

Convert the required input format for MSstats into general format (MSnSet class in MSnbase package) on the proteomics.

Usage

transformMSstatsToMSnSet(data)	

Arguments

data	name of the raw (input) data set with required column for MSstats.

Details

• raw : See SRMRawData for the required data structure of raw (input) data.

• output : After transformation, assayData includes value of Intensity. phenoData has variables of IsotopeLabelType, Condition, BioReplicate,Run. featureData has variables of ProteinName, PeptideSequence, PrecursorCharge, FragmentIon, ProductCharge.

Author(s)

Ching-Yun Chang, Meena Choi, Olga Vitek.

Maintainer: Meena Choi ([e-mail])

References

Meena Choi, Ching-Yun Chang, Timothy Clough, Daniel Broudy, Trevor Killeen, Brendan MacLean and Olga Vitek. "MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments" Bioinformatics, 30(17):2524-2526, 2014.

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.

Timothy Clough, Safia Thaminy, Susanne Ragg, Ruedi Aebersold, Olga Vitek. "Statistical protein quantification and significance analysis in label-free LC-M experiments with complex designs" BMC Bioinformatics, 13:S16, 2012.

Gatto, L. and Lilly, K.S. (2012). MSnbase-an R Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics, 28, 288-289.

Examples

	
library(MSnbase)
quant.msnset<-transformMSstatsToMSnSet(SRMRawData)

lindsaypino/MSstats-patch documentation built on May 24, 2019, 6 p.m.