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Characterising phase variations in MALDI-TOF data and correcting them by peak alignment.

Lin SM, Haney RP, Campa MJ, Fitzgerald MC, Patz EF - Cancer Inform (2005)

Bottom Line: With the help of principal component analysis, we demonstrated that after peak alignment, the differences among replicates are reduced.We compared this approach to peak alignment with a model-based calibration approach in which there was known information about peaks in common among all spectra.Finally, we examined the potential value at each point in an analysis pipeline of having a set of methods available that includes parametric, semiparametric and nonparametric methods; among such methods are those that benefit from the use of prior information.

View Article: PubMed Central - PubMed

Affiliation: Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA. S-Lin2@northwestern.edu

ABSTRACT
The use of MALDI-TOF mass spectrometry as a means of analyzing the proteome has been evaluated extensively in recent years. One of the limitations of this technique that has impeded the development of robust data analysis algorithms is the variability in the location of protein ion signals along the x-axis. We studied technical variations of MALDI-TOF measurements in the context of proteomics profiling. By acquiring a benchmark data set with five replicates, we estimated 76% to 85% of the total variance is due to phase variation. We devised a lobster plot, so named because of the resemblance to a lobster claw, to help detect the phase variation in replicates. We also investigated a peak alignment algorithm to remove the phase variation. This operation is analogous to the normalization step in microarray data analysis. Only after this critical step can features of biological interest be clearly revealed. With the help of principal component analysis, we demonstrated that after peak alignment, the differences among replicates are reduced. We compared this approach to peak alignment with a model-based calibration approach in which there was known information about peaks in common among all spectra. Finally, we examined the potential value at each point in an analysis pipeline of having a set of methods available that includes parametric, semiparametric and nonparametric methods; among such methods are those that benefit from the use of prior information.

No MeSH data available.


Comparison of initial data, FDA-aligned data, and alignment using prior information.
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f4-cin-01-32: Comparison of initial data, FDA-aligned data, and alignment using prior information.

Mentions: We illustrate the first result in Figure 4. The first plot shows unaligned peaks, with the second showing peaks aligned using the approach outlined. The third shows peaks aligned with the help of automated peak finding and then “forced” into alignment using a piecewise linear (linear spline) model. This alignment is in spite of some data for the A5 curve that suggests this replicate is in fact quite different in nature. In the “forced alignment”, modest evidence to the contrary is not allowed to trump the initial prior information guaranteed by the researcher to be correct.


Characterising phase variations in MALDI-TOF data and correcting them by peak alignment.

Lin SM, Haney RP, Campa MJ, Fitzgerald MC, Patz EF - Cancer Inform (2005)

Comparison of initial data, FDA-aligned data, and alignment using prior information.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC2657651&req=5

f4-cin-01-32: Comparison of initial data, FDA-aligned data, and alignment using prior information.
Mentions: We illustrate the first result in Figure 4. The first plot shows unaligned peaks, with the second showing peaks aligned using the approach outlined. The third shows peaks aligned with the help of automated peak finding and then “forced” into alignment using a piecewise linear (linear spline) model. This alignment is in spite of some data for the A5 curve that suggests this replicate is in fact quite different in nature. In the “forced alignment”, modest evidence to the contrary is not allowed to trump the initial prior information guaranteed by the researcher to be correct.

Bottom Line: With the help of principal component analysis, we demonstrated that after peak alignment, the differences among replicates are reduced.We compared this approach to peak alignment with a model-based calibration approach in which there was known information about peaks in common among all spectra.Finally, we examined the potential value at each point in an analysis pipeline of having a set of methods available that includes parametric, semiparametric and nonparametric methods; among such methods are those that benefit from the use of prior information.

View Article: PubMed Central - PubMed

Affiliation: Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA. S-Lin2@northwestern.edu

ABSTRACT
The use of MALDI-TOF mass spectrometry as a means of analyzing the proteome has been evaluated extensively in recent years. One of the limitations of this technique that has impeded the development of robust data analysis algorithms is the variability in the location of protein ion signals along the x-axis. We studied technical variations of MALDI-TOF measurements in the context of proteomics profiling. By acquiring a benchmark data set with five replicates, we estimated 76% to 85% of the total variance is due to phase variation. We devised a lobster plot, so named because of the resemblance to a lobster claw, to help detect the phase variation in replicates. We also investigated a peak alignment algorithm to remove the phase variation. This operation is analogous to the normalization step in microarray data analysis. Only after this critical step can features of biological interest be clearly revealed. With the help of principal component analysis, we demonstrated that after peak alignment, the differences among replicates are reduced. We compared this approach to peak alignment with a model-based calibration approach in which there was known information about peaks in common among all spectra. Finally, we examined the potential value at each point in an analysis pipeline of having a set of methods available that includes parametric, semiparametric and nonparametric methods; among such methods are those that benefit from the use of prior information.

No MeSH data available.