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Messages - Guillermo Quintas

1
Other / Re: Peak alignment with large dataset (over 2500 samples and growing)
Hi, as a workaround I usually split big data sets into subsets (~250 runs) to process them independently using XCMS. Then I use a linear or non-linear (rsc, svr,..) fitting of the shift in the retention time using 'known' metabolites to match variables across peak tables. As said, it's just a workaround but you can process each subset in parallel and reduce (a lot) the computing time and memory needed.
g
ps. if the raw data are already pretty well aligned, peak tables can be aligned using m/z & RT tolerances and a 'master-slave' approach in matlab/R/python/etc
2
Other / Re: Feature intensity drift correction suggestions
Hi,
I would recommend you to use qc-svrc (the function is coded in matlab, if you're interested just send me an email to guira@uv.es). It's non-parametric (SVR) and its use is quite straightforward. Besides, it allows a fitting of the SVR parameters to the instrument performance by using the ε-insensitive loss parameter (for example, if you 'known' that a rsd~10% is acceptable in your instrument, then you can use that value to define the tolerance (as ε-insensitive loss parameter))
https://www.ncbi.nlm.nih.gov/pubmed/26462549
https://www.ncbi.nlm.nih.gov/pubmed/29852994

g.

6
XCMS / Very basic Question on mzML
Hi everyone,
a very basic question but I'd be really grateful if you could help me: I'm trying to load a set of mzML files saved in a single folder into XCMS. So far I tried doing this:
mzMLpath <- ("~/path")
mzMLfiles <- list.files(mzMLpath,recursive=TRUE,full.names=TRUE)

LCMS <-xcmsRaw (mzMLfiles)

what am I doing wrong? Do i need to read each mzML file separately?