Appendix 266 defined here for the experimental samples. A visual inspection of the spectra is performed. A concordance analysis compares a set of 85 feature values from the machine qualification batch with those of the Gold Standard run. Concordance plots for all 85 features, plotting the feature values for the run against those for the ‘Gold Standard’ run, are generated and examined. A summary statistic is computed, which assesses how close the slopes of the 85 concordance plots are to the ideal slope of 1. Qualification metrics assessing spectral quality and concordance of the spectra with the Gold Standard must be met for the mass spectrometer to be qualified for spectral acquisition from experimental samples. c. Spectral Acquisition Spectra were obtained using a qualified MALDI-TOF mass spectrometer (SimulTOF 100 s/n: LinearBipolar 11.1024.01 from Virgin Instruments, Sudbury, MA, USA). The instrument was set to operate in positive ion mode, with ions generated using a 349 nm, diode-pumped, frequency-tripled Nd:YLF laser operated at a laser repetition rate of 0.5 kHz. External calibration was performed using a mixture of standard proteins (Bruker Daltonics, Germany) consisting of insulin (m/z 5734.51 Da), ubiquitin (m/z, 8565.76 Da), cytochrome C (m/z 12360.97 Da), and myoglobin (m/z 16952.30 Da). Spectra from each MALDI spot were collected as 800-shot spectra that were ‘hardware averaged’ as the laser fires continuously across the spot while the stage is moving at a speed of 0.25 mm/sec. A minimum intensity threshold of 0.01 V was used to discard any ‘flat line’ spectra. All 800-shot spectra with intensity above this threshold were acquired without any further processing. 2. Mass Spectral Processing Spectral processing is necessary for two main reasons. First, it is used to average together many of the 800-shot ‘raster’ spectra that were collected on the mass spectrometer to create the Deep MALDI1 averages. This allows a deeper and less noisy probing of the serum proteome. Second, spectral processing is essential to render the deep MALDI average spectra reproducible and comparable across samples. a. Processing of Raster Spectra to Deep MALDI averages Raster spectra were rescaled in the mass/charge (m/Z) axis relative to a standard reference spectrum to correct for any overall alignment issues in m/Z. To improve the signal to noise ratio of the spectra, a ripple filter was then applied. For a finer
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