Finnee: properties and methods

Introduction

The Finnee object is the main object of the toolbox. It contains all necessary information about the file as well as one or more dataset objects.

Properties

• .FileID: The generic name for the Finnee folder.
• .DateOfCreation: The date of creation.
• .FileIn: The full path to the original mzML file.
• .Datasets: An array of Dataset objects.
• .Options: Options used by the creator method.
• .Path2Fin: The path to the finnee folder.
• .MZMLDump: All the information (excluding scans) that were in the mzML file.

Methods

Finnee

The creator method. For more information see Converting an mzML file to a Matlab object.

save

Using this command Will save the Finnee object in the path defined by obj.Path2Fin with the name myFinnee.mat. It is important not to change this name because it allows to automatise the processing of multiple Finnee objects. For example, see .

remDataset

To be done.

duplicateFinnee

To be done.

queryMZMLDump

allow to recover information from obj.MZMLDump. Should be used as myFinnee.queryMZMLDump(string).
string can be 'all' or any id from the MS control vocabulary. For example, with the CE-TOFMS data from a urine sample ,

myFinnee.queryMZMLDump('MS:1000128')

gives

<cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum"/>

exportAs

To be modified. Allow exporting any dataset as a mzML file. Should be used as myFinnee.exportAs(n), where n is the index to the dataset to export.

align2newMZ

This function is used to create a new dataset where all profiles MS scans will be aligned to a common mz axis. This functions could be used as follow:

myFinnee = myFinnee.align2newMZ(n, axis)

where n is the original dataset (normally 1), and axis is the new axis to be used. If axis is empty, the axis will be extrapolated from the most intense scans. For more information, see Scans alignment.

align2newMZ can be used with the various options using this command as follow:

myFinnee = Finnee.align2newMZ(n, axis, options1, param1, options1, param2,...)

where options can be:

• 'tLim'. param is a 2x1 array of reals. param(1) is the starting time at which the scans should be recorded and param(2) then ending time.
• 'spikes'. param is an integer equal to 0 to 3 (default value: 1). With this option, spikes will be removed for each MS scans before recording, where spikes are series of non-zeroes intensities, delimited by zeros intensities values, whose number of points is less or equal that param. By default, singleton points (param = 1) are removed.
• 'masterAxis'. param is a string in the form 'mzStart:mzEnd:Id'. mzStart and mzEnd will be used to define the limit of the axis, Id is the index to the scan that will be used to generate the mzAxis.

filterDataset

filterDataset is used to correct specific datasets. A new dataset will be created with corrected scans. The function should be used as followed;

myFinnee = Finnee.filterDataset(n, method, options1, param1, options1, param2,...)

where n is the index to the datasets. The following methods are for the moment recognised:

• 'removeSpikes:SpkSz'. Allow removing spikes in each MS spectra where spikes are defined as any series of points delimited by null values whose number of points is lower or equal to SpkSz.(1 to 3).
• 'remNoise:dx:dy:thr'. Use to remove background noise. For each point, will oss, centred around the point of interest and of size 2dx+1 in the time dimension and 2dy+1 in the m/z dimension. If the noise has been calculated, The centre point intensity will be set to zero if no S/N within the cross is higher than thr. See Noise removal for more information)
• 'sgolay:wdsz:dt2rem'. Will performed a Savitzky-Golay FIR smoothing filter to the data, in the time direction, with a filter of order one and frame length wdsz. If dt2rem is different from 1, 1 pts every dt2rem+1 pts will be recorded. See Savitzky Golay filtering for more information)

BaselineCorrection

BaselineCorrection is used to correct a full profile dataset from baseline drift. BaselineCorrection can be used with a graphic user interface (GUI), see Baseline correction for more information. BaselineCorrection can also be used with a series of options instead of the GUI. In this case, the format should be:

myFinnee = myFinnee.BaselineCorrection(n, 'Frequency', n, 'Baseline', 'BaselineMethod');

where n is the target dataset, 'Frequency' followed by a real defined the m/z to be corrected from baseline drift, 'Baseline' followed by the string 'BaselineMethod' is used to define the baseline correction algorithm. The following baseline algorithms are recognised:

• 'PolyFit:n'. weighted polynomial fitt, where n is the order of the polynomial
• 'ArPLS:lambda:ratio'. Original arPLS baseline correction algorithm.
• 'ArPLS2:lambda'. Modified arPLS baseline correction algorithm.

doCentroid

allows converting profile scan to centroid scan. doCentroid can only be used with profile dataset and will create a new dataset. The centroid algorithms and its associated parameters should be defined in the method input parameter using:

myFinnee = myFinnee.doCentroid(n, method);

where n is the target dataset and method can be

• 'LocalMax:n:thr'. Detection of local maxima. Local maxima should be separated by at least n points. Accurate masses are calculated by fitting a polynomial of degree m to the peak maxima and its two neighbours. Points of intensity lower than thr are discarded.

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