This is a collaborative project for analysis of mass spectra data
with Universal Prediction Limited (UK) (http://www.universal-prediction.com/).
The information contained in mass spectra, in combination with the level of tumor marker serum CA125 useful for early detection of ovarian cancer (Gammerman et al.,The Computer Journal, (2008))
MS data processing can be used to solve this task.
First step of analysis is data preprocessing that allow to compare MS from different patients and to identify location of peaks.
The Softberry SMS program package allows to perform these procedures are used to be completed in the following order:
Detection of the baseline and its subtraction from intensity;
Once the peaks in different spectra are identified, they can be aligned over each other that allows to reveal the presence of common peaks in these spectra.
More details on analysis of MS data are presented in following WORD document as well as in the PowerPoint presentation.
Also read the Help file for particular programs and consider the associated examples of MS data analysis and its clinical application.
Proteomics-MSBaseline - mass-spectrum baseline detection and removal
Proteomics-MSSmoothing - program performs smoothing of the mass-spectrum data
Proteomics-MSNormalization - program performs signal normalization for the mass-spectrum data
Proteomics-MSPeakAlign - program performs peak detection and alignment for several mass-spectrum samples
Proteomics-MSPeakFind - program performs peak finding in the mass-spectrum data
Proteomics-MSResampling - this program performs resampling of the mass-spectrum data
Proteomics-MSCalibrate - program performs calibration of the
raw mass-spectrum data
Proteomics-MSPreprocess - program performs preprocessing steps for the mass-spectrum data
Proteomics-MSCreateTable - program created data table for linear discriminant analysis
Proteomics-MSCalcParamLDA - program Calculate parameters for linear discriminant analysis of cancer/normal samples using MS data
Proteomics-MSPredictLDA - program performs classification of patient for cancer/normal case using the mass-spectrum data and CA125 marker level