Raw FT-ICR DMS files are very large and are painful to analyse directly. Two reduction methods can be used and combined:
filtering the data to match as well as possible a predefined regular grid
keeping only the data that match a list of targets
Combining both methods might enable to reduce the MS size by nearly 90%, in the usual applications.
The script is controlled by the following parameters:
#==================================================== # User configuration params ========================= #==================================================== ## Data and results directories origMsDir = 'Test_FTICR_2/FTICR' compMsDir = 'Test_FTICR_2/FTICR_compressed' ms_type = 'fticr' ## Compress mode compMode = c('grid','targets','grid+targets') ## Grid specifications mzMin = 70 mzMax = 250 dmz = 0.001 ## Targets specifications tgTable = 'Test_FTICR_2/targets_list.csv' dmzTarget = 0.5 # Delta m/z to keep around target ## Short run to check ? test = FALSE
origMsDir: (string) is the path to a directory containing the
files to treat (all files within the directory will be treated).
compMsDir: (string) is the path to a directory where the
compressed files will be stored.
ms_type: (string) is the type of MS to treat. Only
fticr at the
compMode: (string) compression modality, which can be
targets or their combination
dmz: (numbers) define the regular grid used
for grid selection.
tgTable: (string) is the path to the targets file used for targets
dmzTarget: (number) is the half-width of the m/z interval to keep
around a target. The interval is centered on
ms_ref vales in
tgTable. The width should be large enough to not miss the peaks,
but small enough for efficient compression…
test: (logical) test run only, to check if data are OK.
Note: it is best to store the spectra as compressed .gz files. The disp space is well reduced and all scripts can handle them transparently.