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Accurate peak list extraction from proteomic mass spectra for identification and profiling studies.

Barbarini N, Magni P - BMC Bioinformatics (2010)

Bottom Line: In both cases, the main phase of the data analysis is the procedure to extract the significant features from a mass spectrum.It has been developed principally to improve the precision of peak extraction in comparison to other reference algorithms.It contains many innovative features among which a sophisticated method for managing the overlapping isotopic distributions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Pavia, Italy. nicola.barbarini@unipv.it

ABSTRACT

Background: Mass spectrometry is an essential technique in proteomics both to identify the proteins of a biological sample and to compare proteomic profiles of different samples. In both cases, the main phase of the data analysis is the procedure to extract the significant features from a mass spectrum. Its final output is the so-called peak list which contains the mass, the charge and the intensity of every detected biomolecule. The main steps of the peak list extraction procedure are usually preprocessing, peak detection, peak selection, charge determination and monoisotoping operation.

Results: This paper describes an original algorithm for peak list extraction from low and high resolution mass spectra. It has been developed principally to improve the precision of peak extraction in comparison to other reference algorithms. It contains many innovative features among which a sophisticated method for managing the overlapping isotopic distributions.

Conclusions: The performances of the basic version of the algorithm and of its optional functionalities have been evaluated in this paper on both SELDI-TOF, MALDI-TOF and ESI-FTICR ECD mass spectra. Executable files of MassSpec, a MATLAB implementation of the peak list extraction procedure for Windows and Linux systems, can be downloaded free of charge for nonprofit institutions from the following web site: http://aimed11.unipv.it/MassSpec.

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Peak detection. Example of application of the method for peak detection by local maxima finding.
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Figure 1: Peak detection. Example of application of the method for peak detection by local maxima finding.

Mentions: The proposed methodology calculates the positions of all the local maxima in the representative spectrum, considering them as possible isotopic peaks. In particular, the maximum value is calculated within a moving window of width (m/z)/RPest for each m/z values of the representative spectrum; the set of these maxima forms a "maximal curve". A local maximum of the maximal curve is detected as central point of a region starting where the derivative passes from a positive value to a not positive and ending where the derivative passes from not negative to a negative value. An example of peak detection is shown in Figure 1. For simplicity, the error is calculated assuming that all the ions are mono-charged.


Accurate peak list extraction from proteomic mass spectra for identification and profiling studies.

Barbarini N, Magni P - BMC Bioinformatics (2010)

Peak detection. Example of application of the method for peak detection by local maxima finding.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2967564&req=5

Figure 1: Peak detection. Example of application of the method for peak detection by local maxima finding.
Mentions: The proposed methodology calculates the positions of all the local maxima in the representative spectrum, considering them as possible isotopic peaks. In particular, the maximum value is calculated within a moving window of width (m/z)/RPest for each m/z values of the representative spectrum; the set of these maxima forms a "maximal curve". A local maximum of the maximal curve is detected as central point of a region starting where the derivative passes from a positive value to a not positive and ending where the derivative passes from not negative to a negative value. An example of peak detection is shown in Figure 1. For simplicity, the error is calculated assuming that all the ions are mono-charged.

Bottom Line: In both cases, the main phase of the data analysis is the procedure to extract the significant features from a mass spectrum.It has been developed principally to improve the precision of peak extraction in comparison to other reference algorithms.It contains many innovative features among which a sophisticated method for managing the overlapping isotopic distributions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Pavia, Italy. nicola.barbarini@unipv.it

ABSTRACT

Background: Mass spectrometry is an essential technique in proteomics both to identify the proteins of a biological sample and to compare proteomic profiles of different samples. In both cases, the main phase of the data analysis is the procedure to extract the significant features from a mass spectrum. Its final output is the so-called peak list which contains the mass, the charge and the intensity of every detected biomolecule. The main steps of the peak list extraction procedure are usually preprocessing, peak detection, peak selection, charge determination and monoisotoping operation.

Results: This paper describes an original algorithm for peak list extraction from low and high resolution mass spectra. It has been developed principally to improve the precision of peak extraction in comparison to other reference algorithms. It contains many innovative features among which a sophisticated method for managing the overlapping isotopic distributions.

Conclusions: The performances of the basic version of the algorithm and of its optional functionalities have been evaluated in this paper on both SELDI-TOF, MALDI-TOF and ESI-FTICR ECD mass spectra. Executable files of MassSpec, a MATLAB implementation of the peak list extraction procedure for Windows and Linux systems, can be downloaded free of charge for nonprofit institutions from the following web site: http://aimed11.unipv.it/MassSpec.

Show MeSH
Related in: MedlinePlus