I would like to use the msmsTests package for differential expression analysis of proteins (spectral counts); however, the vignette only covers working with a MSnSet class and not how to get your data into that class.
While the pRoloc vignette does mention how to convert csv files to the R data class MSnSet using the readMSnSet constructor function (section 2.2.2) the problem is when trying to follow either the msmsTests or RforProteomics vignettes they use a different type of MSnSet object which produces different results, for example:
pRoloc creation of MSnSet:
f1 <- dir(system.file("extdata", package = "pRolocdata"), full.names = TRUE, pattern = "exprsFile.csv") f2 <- dir(system.file("extdata", package = "pRolocdata"), full.names = TRUE, pattern = "fdataFile.csv") f3 <- dir(system.file("extdata", package = "pRolocdata"), full.names = TRUE, pattern = "pdataFile.csv") tan2009r1 <- readMSnSet(exprsFile = f1, featureDataFile = f2, phenoDataFile = f3, sep = ",") pData(tan2009r1)
RforProteomics creation of MSnSet:
library("msmsEDA") library("msmsTests") data(msms.dataset) ## Pre-process expression matrix e <- pp.msms.data(msms.dataset)pData(e)
As you can tell the pData() result is different for both of these. It would be nice if I could figure out how to convert the msms.dataset (MSnSet class) to something I can investigate to see how these objects differ - they won't let you investigate using head() or tail(). If I could see what it looks like I could figure out how to convert my data into this class for use in differential analysis and visualization.