Dear developers,
I have some problems using MzMine 2.10 version
for processing my data. Below I will describe you my case:
_My data:_
* Mzmine version 2.10
* Operating systems information: 64 bit;
installed memory (RAM) 8.00 GB ; processor intel (R) Core (TM, i7-3770S
CPU).
* Windows edition Windows 7 Professional.
* Java SE runtime
Environment 8 (jre-8-windows-x64.exe).
* I've only changed the Heap
Size at 7830 MB, according to my computer performance.
* I worked on a
LC-ESI(orbitrap)Mass Spectrometer so I have high resolution files (132
raw files thermo) in MS1 level (Xcalibur version 2.1.1).
_Starting
processing by MZMine 2.10:_
* First step: IMPORT FILES, NO PROBLEM
FOR ALL 132 FILES!
* Second step: DATA SET FILTERING: Crop Filter
(retention time 10 to 26 min) NO PROBLEMS FOR ALL 132 FILES!
* Third
step: MASS DETECTION: centroid (selected noise level 5000) NO PROBLEMS
FOR ALL 132 FILES!
* Fouth step: CHROMATOGRAM BUILDER: min time span
0.0, min heigh 5000; m/z tolerance 0.2 m/z or 20 ppm. THIS PROCESS IS
VERY SLOW BUT THE MOST IMPORTANT THING IS THAT AFTER PROCESSING THE
FIRST 40 FILES A TASK ERROR CONCERNING WITH A PROBLEM WITH THE HEAP SIZE
OF JAVA APPEARS.
I' ve also tried using the TARGETED PEAK DETECTION by
importing a csv file (see attached file cacao.csv) (intensity tolerance
10%; m/z tolerance 0.2 m/z or 20 ppm,; retention time tolerance 2.0
absolute min) but every time i try to apply these parameters to my raw
thermo files a task error telling that my files could not be read or
they are empty appears...but of course this is not true because I can
see their content!
In any of these cases I've used the batch mode.
In the first case (CHROMATOGRAM BUILDER): Do I also have to enhance
the Heap size total memory of Java? Which could be the most suitable
value according to my case?
In the second case (TARGETED PEAK
DETECTION) is there something wrong in my csv file?
Thanks for your
kind help,
Angela Mari
[M-H]-;Rt (min);name
351.12;13.4;1
294.05;16.4;2
497.12;16.98;3
329.08;17.44;4
403.06;17.49;5
409.16;17.8;6
427.17;18.15;7
577.14;18.56;8
378.16;18.87;9
289.07;19.45;10
335.07;19.53;11
865.2;20.37;12
305.06;20.91;13
1153.25;21.15;14
393.17;22.4;15
463.08;23.32;16
737.16;23.49;17
753.16;24.07;18
433.07;24.51;19
427.15;24.97;20
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