Hello,

I am looking to convert data from my LC-MS (Waters G2 Synapt) to netCDF in order to import into another platform.  Unfortunately netCDF is the only import option available.  Waters Masslynx contains a netCDF export tool, however it is hard wired to centroid the data first and I need non-centroided data (profile/continuum).

I can convert to a suitable import format (mzXML for example) using ProteoWizard but then need to convert to netCDF.  One of the PWiz devs suggested that XCMS can do it but I cannot see this explicitly stated in the package literature.

MAIN QUESTION - If I supply non-centroided data to XCMS, can it translate it to netCDF without performing any processing (centroiding, peak picking).

BONUS QUESTION - I will float this to the ethers, but does anyone know of a better tool to get from Waters.raw to netCDF?

BONUS QUESTION 2 - Is there a Bioconductor app in development that could take the output from XCMS (peak picking), identify ESI-MS protein charge state profiles and deconvolute the mass?  The problem I am having is the identification of protein charge state envelopes from a complex LC-ESI-MS run containing dozens or more protein species without relying on chromatographic integration (many proteins are invisible in a BPI trace, too many co-elutions in a TIC chromatogram and there are abundant proteins under flat baseline in TIC chromatograms.

The main question is what I really need answered, the other two are bonus.

Thanks in advance,

Ray

Indeed, you can load the mzML files as a xcmsRaw object and save that using the write.cdf(object, filename) as a cdf file. Assuming that the mzML file is bound to the mz_file variable:

library(xcms)
library(ncdf4)

## Setting profstep to 0 as we don't need to generate the "profile matrix"
xs <- xcmsRaw(mz_file, profstep = 0)
write.cdf(xs, filename = sub(mz_file, pattern = ".mzML", replacement = ".cdf", fixed = TRUE))

Unfortunately I cannot help you with your bonus questions.

cheers, jo