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Data Processing: Data Explorer

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Spectrum view (y-normalized) Mass labels User labels Output windows Data Explorer User Interface Processing history, Base Peak (apex) mass and intensity

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Opening a Data File for Processing 1. Start at “File|Open” 2. Add each file to be opened to the selected list (up to 8 files) 4. Click here to finish and open the selected file(s) 3. Decide which *.set file to use F ile

The Structure of the *.DAT file:

mass spectra (could be more than one) acquisition settings processing settings calibration info result file The Structure of the *.DAT file exportable into *.BIC exportable into *.CAL exportable into *.SET

Useful Data Processing Tools:

Useful Data Processing Tools Basic processing features Peak detection, peak labeling Graphics Resolution, S/N calculators Baseline correction Noise reduction, smoothing Calibration (manual, automatic with the sequence controller) Advanced processing features Calculators (isotope, elemental, AA comp, etc.) Peak deisotoping Macros and integrated VBA support

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Peak Detection/Basic Settings Data types are distinguished by assumed resolution: Mariner: 5000 Voyager linear: 2000 Voyager refl.: 10000 PS1: 7500 Area Threshold Intensity Threshold Pea k s

Peak detection : Application to data with noisy baseline:

w. 2% area threshold w. 2% intensity threshold Peak detection : Application to data with noisy baseline “Noise peaks” are detected because of improper threshold setting

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Peak Detection/Advanced Settings Peak detection parameters can be set independently, range-by-range peak detection ranges Pea k s

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Tryptic digest of E. coli beta galactosidase Peak Detection/Advanced Settings

Insert Peak Function:

Allows you to quickly add an undetected peak to the peak list Insert Peak Function Insert Peak Function detects and labels the peak in the range selected by right click-drag

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Any column can be sorted - Click on heading to sort Displaying the Peak List (Detected Peaks) Spec Peak List tab in Output Window

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Peak List Options Remove an unwanted detected peak by highlighting it in the Spec Peak List and clicking here Right-click on the Spectrum Peak List to enable these options

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Peak Labeling User-defined labels ( e.g., applied by macros or *.lbs files) can be applied, removed or customized here Centroid Mass assignment is more accurate than Apex Click on Apply to preview changes. Click on OK to apply changes and close Note: Peak Detection and Peak Labeling settings are saved in a *.set file Note: Not all detected peaks will be labeled in any given view Pea k s

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User Defined Peak Labeling Pea k s

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Peaks with user labels

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Peak Label Example: Mass Differences between adjacent peaks Polystyrene sample (theoretical difference 104 Da)

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D isplay Spectral Display Options Up to eight spectra can be displayed at once Allows a user-defined mass or intensity range to be displayed Creates two copies of a trace; very useful to compare processed data with original Links zooming functions when two or more traces are displayed “Undo” processing by reverting back to original Spectrum #1 Go to Graphic Options to customize Spectra

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Linking Traces Together Zoom functions are now linked for both traces Comparison of original trace vs Noise Reduction

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Graphic Options D isplay G raphic Options… Note: Graphic settings can be saved in a *.set file

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Data-type dependent defaults Default.set files contain the default information used for peak detection and display. These are found in the Voyager directory and can be changed by the user. VoyagerLinear.set DefaultLinearCal.set VoyagerReflector.set DefaultReflectCal.set VoyagerPSD.set Additional useful peak detection/display (*.set) files for specific data types can be found on the C: drive under Voyager/Settings/Voyager

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Applying optional .set files to your data

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File 1 File 2 Theoretical Isotope Pattern File 2 and the Theoretical Pattern are pasted onto File 1 as traces and linked together To Overlay Traces

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Click on Display/Overlay Traces To Overlay Traces

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Calculated Resolution is displayed in the Output Window Results tab Select peak by right click-drag Using the Resolution Calculator

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Using the S/N Calculator Calculated S/N is displayed in the Output Window Results tab Automatic S/N Calculation Manual S/N Calculation allows user-defined noise selection

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Baseline Correction P rocess Raw Data Corrected Data

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Value can be varied between 2 and 32767, higher value more smoothing sort of, so for broad protein peaks might want to use 1000 or higher etc, for peptide peaks less than 32 or 32 typically Value can be varied between 0 and 1, higher value more local correction being applied. Default value 0.5 works well for most applications Value can be varied between 0 and 1, higher value fits baseline more closely to the data. Default value 0.1 works well for most applications Advanced Baseline Correction P rocess

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Advanced Baseline Correction Raw Data Corrected Data Useful in processing noisy high mass spectra e.g., Protein, DNA samples

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Types of noise reduction Noise Removal ( true denoising) Noise Filtering ( another true denoising) Default ( resolution based smoothing) Gaussian Smoothing ( classical smoothing)

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Noise Removal Noise Removal NR(2.00) This program assumes that noise in the spectrum is white noise . The program reduces random fluctuations that are within the noise range. The noise range is set by the “Std Dev to remove” Number that the program requires. Typically this is set at 2 such that any signal below a 2:1 Signal to Noise ratio (RMS noise definition) is removed. This setting provides very aggressive denoising. A setting of 1 is less aggressive. The technique unlike classical smoothing does not reduce the resolution of the peaks to any significant degree. Provides very aggressive denoising Usually parameterless but may want to adjust from 2 to 1 to avoid spikes. Retains as close as possible original peak resolution Excellent for presentation purposes

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Noise Removal For the smoothing of high resolution data, Noise Removal is recommended raw data With noise reduction

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Noise Filtering Noise Filtering NF(0.7) Unfiltered noise is random and uncorrelated , while signals are highly correlated in that successive Y values progressively reduce from peak tops. The noise filtering program is designed to identify correlated and uncorrelated features in data so that only the uncorrelated noise components are filtered . The degree of correlation is the only parameter and determines how efficiently the noise is filtered with respect to the signals. This value typical varies from 0 to 1 with a common default of 0.7. Minimum resolution loss across peaks is typically observed. Virtually parameterless as default of 0.7 best for most data. Allows resolution to be maintained while reducing noise. Retains small peak features near the baseline

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Default Smoothing Default (gaussian) smoothing RSM200 This function is an advance on classical gaussian smoothing. The filter is changed across the mass range depending upon the resolution setting stated in the peak detection parameters . Classical smoothing will tend to over smooth at the low mass end and under smooth at the high mass end. The program is parameter less, but is dependent on the setting in the peak detection parameters. Best on high mass data where lots of data points across a peak Depends on correct peak detection parameters

Resolution-based smoothing:

Resolution-based smoothing User specifies resolution (under Peak Detection); software chooses number of points to use depending on the mass. 50

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Gaussian Smoothing Smoothing SM353 This the classical smoothing program which allows user interaction via setting the number of smoothing points ( from 3 up to 353). The program defaults to a “suggested” value for the acquired trace ( backhighlighted in blue) for ease of use. This program is a known quantity . Allows user input over a wide range Data output can be compared with other data outputs

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raw data smoothed data P rocess Gaussian Smoothing

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Manual Calibration Peaks from spectrum Reference masses From a *.ref file Select a Reference File (*.ref) Export *.Cal File P rocess

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Dialog to enter calibration masses manually Manually enter calibration mass here if not in *.ref file e.g., to recalibrate spectrum based on database search hit

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Exporting a Calibration File Click here to select a filename and location for the saved *.cal file

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Exporting a calibration from a Data File

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Saving Your Work F ile

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Trace copied to clipboard List of masses and intensities copied to the clipboard Formatted peak list copied to clipboard Additional types of Outputs

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Using the Isotope Calculator A pplications

Isotope Calculator Bovine Insulin at 30,000 resolution:

Isotope Calculator Bovine Insulin at 30,000 resolution

The Ion Fragmentation Calculator:

The Ion Fragmentation Calculator Calculator will: Calculate fragment masses Label fragment peaks Create reference file User specifies AA sequence and fragment types, A pplications

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Elemental Composition

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This is not just a method of removing the mass labels from peaks other than the mono-isotopic peak. This program reports a ‘stick’ spectrum where the only masses represented are those from the mono-isotopic mass and also where the height of that peak is representative of the summation of the areas of the peaks in each determined isotopic cluster. The program calculates the theoretical isotopic pattern at a given mass based on the given theoretical formula ( e.g.C 6 H 5 NO - a minimum common formula for all amino acids). Any deviation from the actual data and the theoretical can yield a hidden peak . The program severely simplifies complex reflector spectra, and is key for database search strategies. De-isotoping DI

Deisotoping:

Deisotoping Deisotoped spectrum can be more efficient for database searching. The deisotoping algorithm uses an assumed elemental composition [n(C 6 H 5 NO) for peptides] to collapse the isotope pattern. overlapping isotope patterns “regular” isotope pattern Monoisotopic masses in overlapping isotope clusters are correctly identified P eaks

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Processing Tools Data Explorer has a vast array of new features which add considerable power to the ability to process MALDI spectra. There are 4 Noise Reduction techniques, of which 2 show particular power in retaining resolution while smoothing data. The Default smooth option allows for a very fast way of smoothing data without setting parameters. The deisotoping tool is a powerful way of simplifying spectra into genuine monoisotopic peaks. Combining both noise reduction and deisotoping allows a dramatic improvement in protein identification from database searching 2D gel digests.

Visual Basic (Macros) in Data Explorer:

Record macros by stepping through procedures (smoothing, baseline correction, deisotoping, etc.). Apply macros before and/or after calibration. Edit macros in Visual Basic if desired. Visual Basic (Macros) in Data Explorer

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Using Macros

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Useful Macros for MS Data Getpeaklist collects peak masses from current view and automatically places list on clipboard. Only the largest 8 peaks per 100 Da are selected. MSFitTag will automatically submit peaks to Protein Prospector MSFit or MSTag. Run_Ladder will sequence DNA, RNA or Peptides Run_PSD will help to interpret PSD or CID spectra

Data Explorer Macro Toolbar:

Data Explorer Macro Toolbar Macro “preset” buttons Show VBA Editor Show Macro Record Stop Assign Macro

Assigning Macros Toolbar:

Assigning Macros Toolbar Assign Macro

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Visual Basic Applications Editor Show VBA Editor

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http://www.nitehawk.com/voyager_macros/ Data Analysis Tools created by using Data Explorer ™ Visual Basic for Applications Conversion to ASCII Delete Peaks MALDI Quantitation Print Options Report Generator SNP Analysis Time of Flight vs M/z Mascot Macro Automated Data Processing Convert .DAT files to .PKM files Note: This website is provided as a convenience to our Biospectrometry Instrumentation users.The software products on this website are not commercial products of Applied Biosystems, are being offered without any charge to the user, and may contain defects or deficiencies. Applied Biosystems is under no obligation to release any software product as a commercial product or to correct any defects or deficiencies or otherwise provide support for any software product downloaded from this website. The information contained is subject to change without notice. All software products are provided "AS IS". Applied Biosystems makes no representations or warranties of any kind, expressed or implied, with regard to the material content or any software product in this website, including but not limited to implied warranties of merchantability and fitness for a particular purpose. Applied Biosystems shall not be liable for errors contained in this material. In no event shall Applied Biosystems be liable for incidental, consequential, special, or indirect damages from or in connection with the furnishing, performance, or use of these software products or material.

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