Hi, To my knowledge there are only 2 packages in R specifically for MS data, mscalib on CRAN, and PROcess in bioconductor devel. The first is for MALDI tof spectrometers and assumes you have picked peaks already and works on the peaks list. The second is for seldi, but the baseline correction and peak picking are pretty generic. To process LC-MS data you have to decide how far back in the device internal processing you want to go. Personally, I have found that the mantra for mass spec data at the moment is "Don't trust vendor software". It mostly sucks. If you can get it you want to be grabbing the data stream as it is read of the column by the sensor, because it helps to warp the chromatagram from each scan so that the peaks align properly. Then you want to conver to m/z. After that comes all the signal processing song and dance, to subtract the chemical noise, make a baseline adjustment, etc. The tools for this in R are here and there and development for processing this stuff is nacent. There is much more available in matlab, which though much more expensive is mostly faster than R. The signal processing community and the chemometrics people tend to work in matlab. Note that it has been my experience that automated peak detection is an art, with more pitfalls than clustering. If you can do anything to avoid that using prior knowledge it helps. Good luck. Nicholas > > Message: 2 > Date: 12 Mar 2004 19:12:32 +0100 > From: Stephen Nyangoma <s.nyangoma@cs.rug.nl> > Subject: [BioC] LC-MS proteomics data > To: bioconductor@stat.math.ethz.ch > Message-ID: <1079115152.10700.12.camel@iwi142> > Content-Type: text/plain > > Sorry for bothering you with this question. > > Has someone analylsed LC-MS data? How do you read this data into R? Are > there preprocessing tools in R? What are the crusial preprocessing > steps? Do the ascii files obtained from Brucker software contain raw > files? Thanks. Stephen. > > > > >