readMSdata: Read LC-HRMS measurement .mzXML data
Description
Initiates an MSlist object and reads LC-HRMS measurement data from .mzXML files.Usage
readMSdata(filepath.mzXML, MSlevel=c(1), progbar=FALSE, minRT=FALSE,
maxRT=FALSE, minmz=FALSE, maxmz=FALSE)
Arguments
filepath.mzXML
Path to the .mzXML file to be read
MSlevel
numeric 1 (MS) or 2 (MS-MS)
progbar
Show a progress bar (TRUE or FALSE)? Might only work in Windows OS
minRT
Filter for measurements with retention time >= minRT. Otherwise set to FALSE.
maxRT
Filter for measurements with retention time
minmz
Filter for measurements with m/z >= minmz. Otherwise set to FALSE.
maxmz
Filter for measurements with m/z
Value
- MSlist
- StateMSlist[[1]]: tags the individual steps the MSlist has undergone.
- ParametersMSlist[[2]]: saves parameter settings.
- ResultsMSlist[[3]]: saves a result summary.
- ScansMSlist[[4]]: matrix with raw measurements (m/z, intensity, RT) and tags for partitions, EIC cluster and individual peaks.
- Partition_IndexMSlist[[5]]: Index assigning partitions to sections in the raw measurment of MSlist[[4]]. Needed for fast (random) access during, e.g., plotting.
- EIC_indexMSlist[[6]]: Index assigning EIC clusters to sections in the raw measurment of MSlist[[4]]. Required for fast access.
- Peak_indexMSlist[[7]]: Index assigning picked peaks to sections in the raw measurment of MSlist[[4]]. Required for fast access.
- PeaklistMSlist[[8]]: Final peak list, cp.
mzpick
Warning
Use plotMSlist to check your data in MSlist for consistency at an early stage before further processing.Details
The return value, a so-called MSlist object, is a simple R list object that contains (a) the raw measurement data, (b) intermediate/final
results of the peak picking procedure and (c) indices for random access, to be passed among functions.
Peaks are nested in EIC clusters which in turn are nested in partitions which in turn are subsets of measurements;
MSlist[[4]] is resorted accordingly during all peak picking steps.
Setting minRT, maxRT, minmz or maxmz allows you to filter your .mzML data.
On the one hand, this may be very useful if only being interested in certain ranges of an experiment.
On the other hand, this allows you to upload subset data of an experiment too large to be loaded into R at once.