Automatic peak identification method
The invention described herein details a protocol to improve analysis and peak identification in spectroscopic data. Bayesian methods are used to automatically identify peaks in data sets. After identifying peak shapes, the method tests the hypothesis that a given number of peaks is found within any given data window. If a peak is identified within a given window, then the likelihood function is maximized in order to estimate peak position and amplitude. This process yields a spectrum with high resolution and minimal artifacts. The method described herein is particularly useful for identifying peaks in data sets obtained from spectroscopy.
1. An automated method of data processing and evaluation comprising the steps of:
(a) selecting a data set having a plurality of peaks contained therein;
(b) developing a hypothesis which predicts a specified number of peaks present within a given window of said data set;
(c) testing the hypothesis that the specified number of peaks is present within the given window;
(d) maximizing a likelihood function to estimate the position and amplitude of said peaks present within the given window;
(e) repeating said steps (b)–(d) for each of a plurality of windows with each of said windows partially overlapping a previous one of said windows wherein peak amplitudes and corresponding positions in said data set are generated using the position and amplitude of said peaks present within each given window so-estimated by each said step of maximizing; and
(f) outputting said peak amplitudes and said corresponding positions to an output device.
2. The method of claim 1 , wherein said step of outputting comprises the step of displaying said peak amplitudes and said corresponding positions.
3. The method of claim 2 , wherein said step of displaying includes the step of overlaying said peak amplitudes and said corresponding positions on a graphic image of said data set.
4. An automated method of data processing and evaluation comprising the steps of:
(a) selecting a data set having a plurality of peaks contained therein, wherein said data set is obtained from time-of-flight mass spectra;
(b) developing a hypothesis which predicts a specified number of peaks present within a given window of said data set;
(c) testing the hypothesis that the specified number of peaks is present within the given window;
(d) maximizing a likelihood function to estimate the position and amplitude of said peaks present within the given window;
(e) repeating said steps (b)–(d) for each of a plurality of windows with each of said windows partially overlapping a previous one of said windows wherein peak amplitudes and corresponding positions in said data set are generated using the position and amplitude of said peaks present within each given window so-estimated by each said step of maximizing; and
(f) outputting said peak amplitudes and said corresponding positions to an output device.
5. The method of claim 4 , wherein said step of outputting comprises the step of displaying said peak amplitudes and said corresponding positions.
6. The method of claim 5 , wherein said step of displaying includes the step of overlaying said peak amplitudes and said corresponding positions on a graphic image of said data set.