GeneMarker manual 1.4 10 2005c - SoftGenetics · 2017. 12. 21. · Figure 4: Processed Raw Data prior to sizing. Analysis & Setting Program Parameters In the wizard, select the template,

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Operation Manual Version 1.4

SoftGenetics LLC Suite 241 200 Innovation Blvd. State College, PA 16803 USA

814 237-9340 www.softgenetics.com

email: [email protected] Technical Assistance: [email protected]

©2004-2005

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Table of contents

Chapter 1 Basic Operation ................................................................................................................................... 4 Software Installation ........................................................................................................................................... 5 Basic Software Operation ................................................................................................................................... 6 Analysis Parameters............................................................................................................................................ 7 Graphical Overview .......................................................................................................................................... 11 Navigation......................................................................................................................................................... 11 Preferences........................................................................................................................................................ 12 Quality Analysis ................................................................................................................................................ 15 Reporting........................................................................................................................................................... 16 Trace Comparison............................................................................................................................................. 19 Overlay View..................................................................................................................................................... 20 Printing Reports ................................................................................................................................................ 21

Chapter 2 Size Template Editor......................................................................................................................... 22 Preparation Requirements ................................................................................................................................ 23 Software Overview ............................................................................................................................................ 23 Getting Started .................................................................................................................................................. 24 Operation & Use ............................................................................................................................................... 25

Chapter 3 Calibration Charts ............................................................................................................................ 26 Preparation Requirements ................................................................................................................................ 27 Software Overview ............................................................................................................................................ 27 Analysis & Functionality................................................................................................................................... 28 Operation & Use ............................................................................................................................................... 29 Migration Time Correction ............................................................................................................................... 31

Chapter 4 Panel Editor....................................................................................................................................... 32 Preparation Requirements ................................................................................................................................ 33 Overview ........................................................................................................................................................... 33 Analysis and Functionality................................................................................................................................ 34 Binning .............................................................................................................................................................. 36 Allele Marker Table .......................................................................................................................................... 39 Operation & Use ............................................................................................................................................... 39 Allele Editor ...................................................................................................................................................... 40 Editing a Panel.................................................................................................................................................. 42 Importing and Exporting Panels ....................................................................................................................... 44

Chapter 5 Fragment Analysis ............................................................................................................................ 45 Preparation Requirements ................................................................................................................................ 46

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Check Size Calling ............................................................................................................................................ 47 Panel Setup ....................................................................................................................................................... 47 Graphic Display ................................................................................................................................................ 50 Reporting........................................................................................................................................................... 50 Printing and Saving........................................................................................................................................... 52

Chapter 6 Pedigree Chart................................................................................................................................... 53 Preparation Requirements ................................................................................................................................ 54 Importing / Linking Pedigrees........................................................................................................................... 54 Opening Pedigree Files..................................................................................................................................... 55 Overview ........................................................................................................................................................... 56 Analysis & Functionality................................................................................................................................... 56 Saving and Outputting Pedigree Files .............................................................................................................. 58

Chapter 7 AFLP Analysis................................................................................................................................... 59 Preparation Requirements ................................................................................................................................ 60 Check Size Calling ............................................................................................................................................ 61 Panel Setup ....................................................................................................................................................... 61 Graphic Display ................................................................................................................................................ 63 Reporting........................................................................................................................................................... 64 Printing and Saving........................................................................................................................................... 65

Chapter 8 MLPA Analysis ................................................................................................................................. 67 Preparation Requirements ................................................................................................................................ 68 Check Size Calling ............................................................................................................................................ 69 Panel Setup ....................................................................................................................................................... 69 Data Normalization........................................................................................................................................... 72 Synthetic Control Sample Calculation .............................................................................................................. 73 Analysis Methods .............................................................................................................................................. 74 Reporting and Printing ..................................................................................................................................... 77

Chapter 9 Quantitative Analysis........................................................................................................................ 79 Preparation ....................................................................................................................................................... 80 Analysis and Functionality................................................................................................................................ 80 Reporting and Saving........................................................................................................................................ 82

Frequently Asked Questions .............................................................................................................................. 83

Chapter 1 Basic Operation

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Gene Marker may be considerably different from other AFLP/Genotyping analysis software that you have experienced. You will find that the majority of the functions have been completely automated, using a “smart” software approach to eliminate the need for constant analyst intervention, and to improve analysis-to-analysis consistency. The software utilizes an intuitive logic flow as indicated by the program icons on the initial tool bar. Chapter 1 Contents Software Installation Basic Operation Analysis & Setting Program Parameters Data Processing Settings Graphical Overview Navigation Quality Analysis Reporting Trace Comparison Overlay View Printing and Saving


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Software Installation To install the software, please double click on program icon, select directory if different from default, and follow installation Wizard.

Once the software has been downloaded, click on the icon to install the software. When you open the software the first time, you will be prompted with a window to register the product (Figure 1).

Figure 1: Registration Window

The User ID is unique to each software key and will be automatically loaded when the window appears. Please locate the Account, and Password on the software CD you received. You will need to enter your Account, Password, and a valid email address. Leave the Registration ID box blank and click Register. You will receive an email with your Registration ID provided. Please enter only the User ID and Registration ID and click Register. After following these steps your software has been successfully installed and registered.


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Basic Software Operation

Data Entry To begin data analysis, click on the Open File icon in the tool bar as indicated by the orange arrow, or follow the Analysis Wizard (green arrow) that will walk you thru the analysis step by step. (Figure 22)

Figure 2: Opening dialogue box

Click on the Add button as indicated in Figure 3. Select folder and data for analysis. Browse for data for analysis by clicking on drop down menu. After locating data click on the Open, highlight up to 1,000 lanes of data for processing. To add all the files in the folder, hold down they keys Control + A while highlighting one file. Click on the Open button. Add or remove samples for analysis by highlighting and clicking appropriate button. When completed, click OK to add data into memory.

Figure 2: Add files Dialogue Box To begin analysis, click the green arrow in the tool bar (Figure 5). The GeneMarker Wizard dialogue box will activate. To view raw electropherogram of each lane, click on the left hand sample column. Click the green run arrow to begin analysis.


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Figure 4: Processed Raw Data prior to sizing.

Analysis & Setting Program Parameters In the wizard, select the template, size standard, standard color and type of analysis (Figure 5). To create a new template, click on the dot indicated by the green arrow. The template can also be chosen from the list of available templates at the left. The Panel can be selected from any available in the drop down box, or can be viewed by clicking the Panel Editor’ button to the right of the drop down, or can be opened from a directory by clicking the directory folder button. The size standard can also be selected from all available from the drop down box and viewed by clicking the Size Template Editor Button to the right. Selecting the correct size standard is crucial for proper data alignment. IMPORTANT: Choose an analysis type from either Fragment (diploid), Fragment (Polyploidy), SnapShot, AFLP, or MLPA. When finished, click on the Next button.

Figure 5: Template, Panel, Size Standard, Color, and Analysis Type Selection

Panel Editor

Analysis type selector


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The Data Processing dialogue of the Gene Marker Run Wizard will activate (Figure 6). This portion of the Wizard is used to select the appropriate settings for analysis. See Basic Process Options for definitions.

Figure 6: Data Process Window.

Data Process Options 1. Analysis Range: The range in camera frames can be manually set, or the software will automatically find the processable data range. Please select desired option. If manual range is clicked on, set the starting and ending frame number of the data set for analysis. 2. Base Line: The software permits the option of either smoothing the data, which will eliminate the smaller noise peaks, or removing the base line completely which will raise the Y-axis above the noise level. Choose the option that best fits your data or analysis requirements.

Figure 7: Before Baseline Subtraction (left) and after Baseline Subtraction.


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3. Peak Saturation Correction: If this option is chosen, the software will analyze saturated data points by creating a synthetic estimate of the peak shape based upon the curves prior to saturation. The results of this data will be less accurate than that of non-saturated peaks.

Figure 8: Before Peak Saturation Correction (left) and after Saturation Correction

(right). 4. Pull-up Removal: This function removes peaks caused by wavelength bleed through to other wavelengths. It is recommended to always use this function.

Figure 9: Before Pull-up Removal (left) and after Pull-up (right). 5. Size Calling Algorithm: GeneMarker offers two alternative sizing methods:

A. Local Southern is a method used in most genotyping software applications, and is recommended for most analysis. (For details on the algorithm, see: E.M. Southern (Southern, E. M. "Measurement of DNA Length by Gel Electrophoresis." 1979. Analytical Biochemistry. 100, 319-323.) B. Cubic Spline Method is offered as an alternative method that may be more appropriate for some data. (For additional information on the Cubic Spline, methods please see: The Astrophysical Journal. December 1, 1994. 436, pages 787-794. Again, we suggest the use of the Local Southern method. However for some data, the Cubic Spline method may be more appropriate.

6. Allele Call Range: Defines the range of the allele calls in base pairs. There are two options:

A. Select Auto Range and the software will display each lane’s processable data range. B. To select a specific analysis region, de-select the Auto Range feature, and input the desired base pair range. Additionally, if the automatic size call fails due to high saturation, deselect auto-range and manually input required data range.


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7. Peak Detection Threshold: (please see individual analysis chapters for recommended initial settings): A. Intensity: Minimum count of the peak height used for peak detection B. Percentage: Relative minimum intensity of allele peaks to the highest peak in the lane used for peak detection. C. Local Region Percent: Defines the minimum peak detection threshold based upon the percentage of the highest peak in that marker. For example, if the threshold is set to 33% the height of all allele peaks must reach at least 33% of the height of the highest peak in that locus.

8. Stutter Peak Filter: Allows the removal of forward and reverse stutter peaks commonly caused by PCR/chemical reactions. The settings are in % of the primary peak. The default settings will remove stutter peaks within 2.5 bp of the primary peak. 9. Save Setting Changes: Saves any user defined setting changes from the defaults that can be recalled for consistency of analysis on similar data sets. 10. Recall Default Tab: Recalls any previously user set or if unsaved the program default settings. Additional Settings Dialogue Box (Figure 10) Permits the selection of a lane containing an Allelic ladder and the Allele Peak Confidence Score range. Select Allelic Ladder lane and modify any required settings prior to clicking Ok. The software will then perform analysis based upon the set parameters in the previous 3 windows. Allelic Evaluation Score: User definable confidence level of the allele call. Reject appears in red, Check appears in yellow and Pass appears in green color code. See individual analysis chapters for recommended settings.

Figure 10: Analysis Comments Dialogue Box


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Graphical Overview following Data Processing

Figure 11: Graphical View of data analysis with gel image

Navigation 1. Zoom In / Zoom Out Expand the image by drawing a box over the electropherogram from right to left while holding down the left mouse key, or by using the + magnifying glass icon. To reduce the image, draw a box from right to left over the electropherogram, or use the - magnifying glass icon. 2. Horizontal Movement: Use the top slider bar to scroll, or hold right mouse button and drag the trace. 3. Report Viewing: The analysis report can be visualized by left mouse button grabbing the grey vertical line separating the report from the analysis electropherograms and dragging the grey line to the left. 4. Electropherogram Viewing: The software will display multiple electropherograms

by double clicking on the sample or samples of interest. A check mark will appear and the electropherogram (s) will be displayed. Use the page down or page up function to sequentially review the processed electropherograms.

5. Navigation:

Figure 12: Navigation Icons


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Navigation Icon Definitions: A. File Open: Opens data input dialogue box to commence analysis. B. Run: Opens Setting Wizard for processing the data. C. Display Toggles: 1. Displays or hides Sample Names. 2. Displays or hides Gel Image. 3. Displays or hides text Analysis Report. D. Print: Sends text report to printer. E. Dye Color Toggle: Allows selection of all colors or singular dye layer. F. Zoom Controls: Expands or contracts Electropherograms. G. Calibration Charts: Displays linearity of lane analysis H. Lane Chart Toggles: Displays or hides text of lane analysis. I. Save Peak Table: Saves the peak table as a text file. J. Event Log: Displays each lane’s processing success or failure. K. Wizard: Activates runtime wizard for the program. L. Save Report: Saves the Allele Report as a text report. M. Report Settings: Allows the user to alter the settings for the report. N. Allele Call: Call alleles by sample(s) or by marker.

View Controls

Figure 13: View Control Drop down menus

Upon activating View on the menu bar, a drop down menu will appear. The first three navigators display or hide various portions of the displayed output as described above. Activating the Preference portion of the menu permits setting general display and start up settings (Figure 13).


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Analysis Preferences The View Settings tab is used to set the precision of the data, in tenths of base pairs, maximum number of open data charts, the maximum number of lane electropherograms that can be viewed in one screen, and finally the maximum numbers of Allele label layers.

Figure 14: Start-Up settings of Program Preferences

Start-up Methods /Settings A. Classical: Is appropriate for experienced users. The user will move through the program data input, settings, and display options without prompting, by following the program’s sequential analysis flow. B. Wizard: Activates GeneMarker Analysis Wizard that will guide the user through the program’s operation. This setting is best for the inexperienced user. C. Show Navigator: Provides option for displaying or not displaying lane identification in the initial view following data processing. D. Show Gel Image: Activates the gel image of the entire analysis so that it is shown immediately upon processing. Display Settings A. Decimal Precision: Select 0-2 decimal places for peak size labeling. B. Mark Off-Allele as ‘OL’: Choose to label alleles that are outside of allele ranges with either size or ‘OL’. C. Max. # of Open Charts: Select the maximum number of charts you would like to toggle between. D. Max. Chart # in Page: Select the maximum number of charts you would like to view at one time (0-8). E. Max. Allele Label Layers: Select the amount of allele label layers to view at one time (0-6). This determines how far you must zoom in to clearly read neighboring allele labels.


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Others A. Automatically Sort Report: Check this option to have the report automatically re-sort every time you modify alleles. Turn feature off if you want the report to remain as sorted until you choose to re-sort. B. Auto Scroll links Alleles When Selected in Report: You may choose whether to scroll to alleles in the trace when you select the allele in the report. Leave this feature on to have the software automatically call up alleles in the trace when you double click on them in the reports.

Figure 15: The Project Menu allows several program actions to be selected

A. Run: Begins data processing setup in the software sequence, allowing user to select/adjust program settings in a sequential manner. The process action can also be accomplished by clicking on the green arrow of the tool bar B. Auto Run: The software will process data using the last set of parameters selected. If one or more of the parameters require changing to improve analysis, change the settings and re-process the analysis by clicking on the Options icon in this pull down menu, and then change desired setting or settings. C. Print Report: Provides various report-printing options. The software permits printing of the sample electropherograms. You can choose to print all samples, or only some samples, and also print samples along with the allele table, if desired. The software will print all colors of one sample per set or a mixture of all colors (See Printing below). D. Options: Allows you to access and change the Run Wizard parameters. E. Project Comments: Allows you to write your own, free form comments regarding the analysis. These comments can be saved and printed.


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Quality Analysis GeneMarker provides a lane quality scoring and linearity analysis (Figure 16). Use the scroll button to view the linearity of each lane’s data. Please see Chapter 3 for complete review of quality analysis function.

Figure 16: Analysis Quality Scoring Disabling poor quality lanes: In addition to the Quality Analysis method using the Calibration Charts, it is also possible to manually disable a file from analysis, without removing this file from the project or list of sample files. Once disabled, these files will not appear in the reports or printouts. In order to disable files, right mouse click on a file in the sample file tree, and select Disable. Once files have been disabled, you may right mouse click and select Enable to include these files in reports and printouts again.

Figure 17: Disable sample files by right mouse clicking and selecting “Disable”.


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Reporting GeneMarker saves analysis results, user comments, raw data, reports and any into a SoftGenetics Project Files (.sgp). Projects can be recalled without re-processing by using the Open Project command or Reopen Project in the File menu. The software has various reports that can be saved as text files to be imported into such programs as Microsoft® Word, Excel, Notepad, etc. The reports include an Allele List, Marker Table for Fragment, Bin Table for AFLP and MLPA data, and an Allele Count. When the option Abide by Panel is chosen the report will show only those alleles detected that match the user specified panel. Also, reports display only alleles with scores in the Reject and Confirm ranges when Show Uncertain Alleles Only has been checked.

Figure 18: Allele Report Settings Window. 1. Allele List: The allele list displays a complete allele list for each dye in every sample.

Figure 19: Allele List Report.


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2. Marker Table (Fragment Analysis): The fragment report is for Microsatellite data and displays the alleles for each marker separately or together for every sample.

Figure 20: Marker Table Report. 3. The Bin Table Report (AFLP and MLPA): The report can either display peak intensity for each detected allele peak or represent the presence, absence, and questionable presence of allele peaks with symbols 1, 0, and ?, respectively.

Figure 21: Bin Table Report for AFLP and MLPA The user may define the specific alleles and/or dyes to output in the report by clicking Bin. After clicking Customize Report, the user may then right click on the allele number to identify the alleles for output and click on the desired dyes. Click OK, and the customized report will be displayed.


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Figure 22: Customized Report for AFLP and MLPA data analysis. 4. Allele Count Report: The Allele Count Report displays the number of detected alleles within each marker for every sample.

Figure 23: Allele Count Report.

5. Allele Peak Table: The Allele peak Table is accessible by clicking the icon indicated by the red arrow. The user may choose which columns to display by right clicking in the

chart. The allele peak table can be saved as a text file by clicking the icon located in the toolbar.

Figure 24: Allele Peak Table.


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Trace Comparison The Trace Comparison function is designed for AFLP data in order to identify length polymorphisms between closely related species. The trace comparison tool is accessible through the Applications menu in the main toolbar. The trace comparison function uses Poisson distribution to calculate significant allelic differences between samples or closely related species. The software calculates and displays the allelic differences between a user defined reference and the sample traces in a histogram below each sample electropherogram. The Trace Comparison Report presents the loss, equivalent and gain of allele peaks, and can be saved as a text file to be imported into Excel for printing. The Poisson Difference thresholds have default settings of Loss<-.20<Equivalent<0.20<Gain, but may be altered by the user for a narrower or wider range.

Figure 25: Trace Comparison with histogram displaying allelic differences.


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Overlay View The Overlay View allows users to graphically display any combination of samples and dye colors. This feature includes a 2-Dimensional (Figure 26) and a 3-Dimensional (Figure 27) view of the selected samples.

Figure 26: 2-Dimensional Overlay View of 15 sample files with dye colors blue, green, and yellow.

Figure 27: 3-Dimensional Overlay View of 15 sample files with dye colors blue, green, and yellow.


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Printing Reports Printing Reports: The software offers several printing options (Figure 28). If Selected Samples is chosen, the software will print out the lanes checked in the file manager. Select the information to be printed, choose the lane electropherograms, peak table, or both and the dye colors you wish to print. By checking the Mix Dyes option, a mixture of all the dyes for each chosen sample will be printed on the same page.

Figure 28: Print Report options and Print Preview of Blue Marker.

Chapter 2 Size Template Editor

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Chapter 2 Size Template Editor Size Template Editor is a function of GeneMarker that will allow the user to check their sample files against a selected size standard, modify and save the size standard for future use, or even create a completely original size standard from scratch. The Size Template Editor function is extremely useful for customers whose analysis requires a customized size standard or a modified version of a typical size standard. This function is simple to use, yet provides the user with a great deal of control over precision analysis of sample data. Note: (New users please read Quick Start Guide Section 1 before proceeding) Chapter 2 Contents Preparation Requirements Software Overview Getting Started Operation and Use


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Preparation Requirements

Size Calling is not necessary to run the Size Template Editor. The Size Template Editor can be run before or after the Size Calling is performed, depending on the user’s needs. The software allows the creation of custom size standards. If a customized size standard is required do not run Size Calling. Create an entirely new size standard utilizing the Size Template Editor, see page 25 for details. To use a modified size standard, first run the Size calling with the standard that is to be modified, then use the Size Standard Editor to make the necessary changes and save the revised standard under a new name.

The Size Calling function is activated by clicking the green play button on the GeneMarker toolbar. This launches the Run Wizard. The first page is for Template Selection. The user must be sure to use the correct size standard for their data and click Next. Then next page is for the user to specify the data process options that they desire, and then click Next. The last page is for additional setting, then click OK. More information about setting GeneMarker program parameters can be found under the heading Analysis & Setting Program Parameters.

Software Overview

The Size Template Editor has a basic, easy to use page layout. On the left side of the screen are navigation trees allowing easy access to specific size standards and sample files. The right top of the page is the Reference Size Standard Electropherogram Trace, the Actual Size Data from the selected sample below that, and the Recognized Size Table. Any of these sections of the page can be resized for a better view of desired data by clicking and dragging the borders of the partitions. The Size Template Editor Screen layout is set up as follows:

Figure 29: The Size Template Editor screen using Size Standard HD400.


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Getting Started

Creating new Size Standards. A user has the ability to create a new, personally customized size standard. This can be accomplished by either clicking the button, or clicking File, then Create New Size Standard in the Toolbar. Enter a name for the size standard. This will create a completely blank size standard. The user is able to select exactly where the size markers should be and insert them manually.

Figure 30: A new Size Standard in the top panel and a sample with alleles displayed in the

bottom panel.

To insert a peak in the new size standard, right click on the horizontal axis where you would like the peak to appear. A window will appear allowing you to change some settings and set the reference size marker more precisely. Size Editor Window The size editor window allows the user to type the exact position of the size marker they would like to insert with more precision. Users can also record comments about the Size marker and decide whether they would like it to be enabled or disabled.

Figure 31: The Size Editor is used to inserted size markers at specific sizes.


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Operation & Use Modifying an existing Size Standard If a size standard has already been created but needs modifications, the user may select the size standard they would like to change from the Available Size Standard Tree and modify the existing panel accordingly. A size marker can be added, deleted, or modified from any existing size standard, by left clicking on a size marker. The triangle above the peak marker will turn from green to yellow, and right clicking will allow the size marker to be inserted, deleted, or edited. Another way to add, delete, or modify a size marker is to right click the desired marker in the size marker table. The same popup menu appears with the options to Insert Delete or Modify a size marker.

Figure 32: Modification of an existing Size Standard

Selecting Sample Files Sample files can be viewed one at a time by double clicking the sample file name from the Sample File tree. The sample file can then be compared against the selected size standard. Peak size markers can be added to the sample file if needed, but this is not expected purpose of the Size Template Manager. To add, delete, or modify the peak size markers in the sample files, the Calibration Charts function should be used (Chapter 3). Size Match Button

The Size Template manager also has a Size Match button . If the user decides that a different size standard is preferred than the one that is selected, select a new size standard from the Available Size Standard Tree. Clicking the Size Match button places the green size marker triangles on the peaks of the sample trace matching the markers with the selected size standard.

Chapter 3 Calibration Charts

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Calibration Charts is a function of GeneMarker that will allow the user to check the software’s accuracy and make necessary modifications to the application’s analysis of sample data. This function is simple to use, yet provides the user with a great deal of control over the analysis of sample data. This function becomes extremely useful when alignment of sample and expected sizes are critical.

Chapter 3 Contents Preparation Requirements Software Overview Analysis and Functionality Operation and Use Migration Time Correction


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Preparation Requirements Note: (New users please read Quick Start Guide before proceeding) Prior to using the Calibration Charts function, the user must have already started a GeneMarker analysis or opened an existing project or opened specific stored data. Size Calling must be performed on the data before viewing the data in the Calibration Charts.

The Size Calling function is performed by clicking the green play button in the GeneMarker toolbar. This launches the Run Wizard. The first page is for Template Selection. The user must be sure to use the correct size standard for their data and click Next. The second page is for the user to specify the Data Process Options that they desire, and then click Next. The last page is for additional setting, then click OK. More information about setting GeneMarker program parameters can be found in the Quick Start Guide under the heading Analysis & Setting Program Parameters. Once this is complete, the Calibration Charts’ complete functionality is available to the user.

Calibration Charts can be accessed by clicking the Calibration Charts button on the main GeneMarker page.

Software Overview The Calibration Charts page has a basic, easy to use page layout. On the left partition of the window, the sample names and scores are listed and numbered from the sample files. The right partition is split into 3 sections. The top section shows the expected size from the reference file created when the Size Calling function is performed. The middle section shows the actual sized data from the selected sample file. The bottom section shows (reference size)/ (actual frame data) graphs for the selected sample files. Any of these sections of the page can be resized for a better view of desired data by clicking and dragging the borders of the partitions. The Calibration Charts screen layout:

Figure 33: Calibration Charts screen displaying linearity of each lane’s data.


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Analysis and Functionality Selecting Sample Files To select a specific sample file to view, click the left mouse button on the desired sample file in the Sample File and Score List. The sample file that is currently being viewed will have its name shown in red, both in the Sample File list and above the corresponding Size/Frame graph. To browse through the samples quickly, the user can use the up and down arrows on the keyboard. Ordering the Sample File and Score List The Sample File and Score List can be ordered in a few ways. Initially it is ordered descending by sample score, meaning the highest (best) score is first and lowest (worst) is last. The files can be ordered ascending by score by left clicking the Score header at the top of the column. Click the Score header again to return to ascending listing. To sort by sample file name in alphabetical order, click the Sample Name heading at the top of the column. To sort by sample file name in reverse alphabetical order, click the Sample Name heading again. Sample Scoring A score is automatically assigned to each sample when Calibration Charts opens. This score (ranging from 0 to 100) corresponds with how well each sample’s data size aligns with the expected size (which was determined when running the ‘Size Calling’ function). A score of 100 would indicate 100% similarity or an exact mach, while a score of zero would mean the sizes do not align properly. The score for a specific sample file can be improved manually by the user. See the Sample Size Alignment Peak Marker Manipulation section of the manual for information about improving sample scores. Mark As Failed If a specific sample file has a particular un-repairable low score due to bad data, the user can decide to mark the sample as failed by right clicking the file name or score in the sample list and selecting Mark as Failed. This will give that sample file a score of 0.

Figure 34: Mark as Failed is used to label bad data with an un-repairable low score. Chart Layout The layout of the Size/Frame Graphs partition can be changed depending on how many graphs the user prefers to view simultaneously. The default layout is a 3 by 3 matrix of Size/Frame graphs, which allows the user to view 9 graphs at one time. To change the layout, the user can click options button. This will open the options window where the number of graphs per row and columns can be changed. The minimum number of graphs per column or row is 1 and the maximum is 5. The Auto Size Fit option is automatically selected (recommended).

Figure 35: Chart Layout Options


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Operation & Use Sample Size Alignment Electropherogram Navigation Navigating through the electropherogram and the expected reference window is quite simple. The conventions are the same as all of SoftGenetics programs:

Zoom In / Zoom Out: To zoom in on a specific area of interest, left click at the top left corner of desired data and drag the box to the lower right corner of the area. To zoom out, left click anywhere and drag the box from the right to the left. This will restore the original un-zoomed view. Horizontal Movement: To scroll horizontally, hold the right mouse button on any part of the electropherogram and drag the mouse along the trace to the desired location.

Sample Size Alignment & Peak Marker Manipulation To achieve better sample size peak alignment to the expected reference standard, Sample peaks can be added, deleted or modified. The more accurate the peak placement on the electropherogram, the better the alignment with the expected reference markers, the higher the score will be for that sample file. To add a peak, right mouse click anywhere on the electropherogram and select ADD. Enter the desired peak position into the pop-up box click OK. To remove a peak, select the green triangle of the peak to be removed, right click and select DELETE. After making all required changes right mouse click on the sample electropherogram and click on UPDATE CALIBRATION. To make adding peaks easier for users, a green vertical line will appear when the electropherogram is clicked. When the user right clicks the trace the green line will show exactly where in the graph the peak will be inserted. Repositioning Peak Markers If a peak marker does not appear at the true peak of a curve, the peak marker can be moved to the correct location. To reposition a peak marker, zoom in on the specific marker and hold the control key on the keyboard. While holding down the control key, click and hold the left mouse button on the desired peak marker and slide the marker along the trace until the marker is positioned at the center of the peak.

Figure 36: Repositioning markers to the center of the peak.


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Examples:

Figure 37: Raw Sample Data has missing and incorrect peak markers:

Figure 38: Zoom in, delete errant peaks and add missing peaks.

Figure 39: Update Calibration and view new score.


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Browsing Through Sample Calibrations: To quickly browse through sample calibration alignments and graphs, use the up and down arrows on the keyboard. This moves through the sample files sequentially, displaying their electropherograms and highlighting their (reference size)/ (actual frame data) graphs. Chart Synchronize Button: Often the user wants to have the Expected Size Alignment Reference window constant so that it can be viewed for quick reference while working with the sample size alignment electropherogram. This is the setting which the calibration charts page takes initially, meaning that the sample size alignment can be zoomed in/out of and scrolled horizontally while the Expected Size Alignment reference stays steady in an un-zoomed view. But there are also times when the user would like the Expected Size Alignment reference window to be synchronized with the sample size alignment window. This is when the Chart Synchronize Button is used (Figure 40). When this button is activated, both windows (Expected Reference Size and Sample Size Alignment) become synchronized. This means that when one window is zoomed in/out or scrolled, the other window will perform the same action simultaneously.

Figure 40: Chart Synchronization

The space ratio between the expected reference sizes and the actual sample peaks should ideally be the same. If this were the case, the sample’s score would be 100 and the Size/Frame graph for that sample would be a perfectly straight line. Anytime the peaks are edited and the calibration is updated in the sample electropherogram, the Size/Frame graph is also updated. As you can see, the Calibration Charts function is very useful when comparing or aligning a specific reference size standard with sample data files. The predetermined peaks are easily deleted, modified, or added depending on the user’s needs using the calibration charts functionality

Migration Time Correction, Megabace systems only The software uses an algorithm designed for Amersham gels that performs a correction for migration times. This algorithm corrects the curvature of migration times in order to make more linear migration time slopes. For this reason, it is recommended to use ESD files, which the software corrects, rather than SCF files, that the software cannot correct.

Chapter 4 Panel Editor

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The Panel Editor is a function of GeneMarker allows the user to check the software’s accuracy and make necessary modifications to the application’s analysis of sample data. This function is simple to use, yet provides the user with a great deal of control over the analysis of sample data. Chapter 4 Contents Preparation Requirements Software Overview Analysis and Functionality Binning Allele Marker Table Operation and Use Allele Editor Editing a panel Importing and Exporting panels


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Preparation Requirements Prior to using the Panel Editor function, the user must have already started the GeneMarker application and either opened an existing project or opened specific stored data. More information about how to open projects or data can be found under Basic Software Operation (Chapter 1). Size Calling must have been performed on the data before viewing the data in the Panel Editor. The Size Calling function is activated by clicking the green

play button in the GeneMarker toolbar. This launches the Run Wizard. The first page is for Template Selection. The user must be sure to use the correct size standard for their data and click next. The next page is for the user to specify the data process options that they desire, and then click Next. The last page is for additional setting, then click OK. More information about setting GeneMarker program parameters can be found under the heading Analysis & Setting Program Parameters. Once this is complete, the Panel Editor can be accessed by selecting the Tools dropdown menu Panel Editor.

Overview The Panel Editor has a basic, easy-to-use page layout. On the left side of the screen are navigation trees to allow easy access to specific panel components and sample files. The rest of the page is made up of the Allele Electropherogram and the Allele Table. Any of these sections of the page can be resized for a better view of desired data by clicking and dragging the borders of the partitions. The Panel Editor Screen layout is set up as follows:

Figure 41: Layout of the Panel Editor screen.

Available Panels Allele Electropherogram

Sample File Tree Allele Table


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Panel Type Getting Started The first thing that should be done is creation of a panel. This can be done by either clicking the button, or clicking File, then Create New Panel in the toolbar. Enter a name for the new panel. You can select the specific panel type desired and method (Automatic and Use All Samples is suggested).

Figure 42: Create New Panel Window Existing Panel Modification If a panel has already been created but requires modification, select the panel they would like to change from the Available Panel Tree and modify the existing panel accordingly.

Analysis and Functionality Selecting Sample Files

Select the files to be used in the Sample File Tree. All files with a check are included in the

panel, and files with a page are not selected. The selection or de-selection can be toggled by double clicking on the file or right clicking, which shows options to select, de-select, select all, or de-select all. The samples can also be sorted in two separate ways. The user can right click the sample, go to Sort By, and select either Sample Name or Size Score. The files are initially sorted by Sample Name.

Figure 43: The selection, de-selection, and sorting of Sample Files for the panel.


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Sequential Sample Browsing To browse through the sample files viewing the electropherogram one by one, select a single sample file from the sample file tree and use the Up/Down buttons on the keyboard to move through the sample files sequentially.

Electropherogram Views Two different electropherogram modes can be toggled in panel manager, Max & Average mode and Include All mode. The Max & Average mode is a single electropherogram display created from the average of all selected files with the max trace of all the selected files (in a darker color). The Include All mode is a way to overlay all of the electropherograms from all of the selected files simultaneously. These selected electropherograms are overlapped and displayed for comparison of multiple sample files.

Average Mode: Include All Mode:

Figure 44: Two different modes are available for viewing in the Panel

To quickly view a specific marker range in the electropherogram, expand the panel assigned to the samples of interest in the Available Panel Tree and select a specific marker range by left clicking on it. This will show a localized view of the marker range in the electropherogram. After zooming out, the other ranges will be inactive. To activate one of these other ranges, double click the range name bar, all others then become inactive.

Figure 45: Viewing a specific marker range in the electropherogram.


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Binning The toggle view button can also be used to toggle the Gel Image view in Panel Editor. If the button is clicked another time, the Gel Image view is shown. In the Gel Image view the user is able to monitor, add, delete, move, resize, or modify bins. The Gel Image navigation in Panel Editor functions like the Gel Image in the GeneMarker main window, except for the bin manipulation. Full View Zoomed View

Figure 46: The full view and zoomed view of marker Blue 3.

Once you have zoomed in on a specific area of interest, adding, deleting, moving, resizing, or modifying bins becomes a simple task. To Insert a Bin: right click on the desired area and click Insert. A window will appear allowing the user to enter specific information about the bin to insert. After the bin is inserted, it can be moved by holding the Shift key and clicking and holding the left mouse button inside the bin. The bin can then be dragged anywhere in the gel image. A small vertical green line indicates the center of the bin.

Figure 47: Insertion of a bin in the panel.


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To draw a Bin: Hold the Shift key; click and hold the left mouse button while dragging the cursor over the desired area. The allele editor window will automatically open to verify your bin settings.

Figure 48: The Allele Editor Window for modifying and/or adding a bin.

To Delete a Bin: Right click on the Bin and Select Delete Allele.

Figure 49: Deletion of a bin in the gel image.

To Change the Size of a Bin or Range Selecting: Hold the shift key on the keyboard and move the mouse over the right or left vertical line of the Bin; the pointer will turn into a two directional arrow, which allows the user to left click and drag either side of the Bin. Another way to change the size is to right click on the allele and left click edit.

Figure 50: Changing the size of a bin or selecting a range for a bin.


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Change the Left and Right sides of the Bin by manually entering the desired range.

Figure 51: Modification of the size of a bin using the Allele Editor.

To Make Changes to a Group of Bins, hold the Ctrl key and Right OR Left click the mouse and drag from left to right until all the desired bins are shaded. The user can then left click on the shaded area and changes the group of alleles.

Figure 52: Modifying a group of alleles. At this point verify whether the software was able to identify the correct markers for the data by comparing the electropherogram in the panel manager with the Gel Image in the GeneMarker main window.

Figure 53: A sample gel image displaying allele markers and size standards.


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Allele Marker Table For convenience, the allele marker table and the allele electropherogram are directly linked. This means that if you select an allele marked in the allele table, the allele marker will turn blue in the electropherogram, and if the allele is double clicked in the allele table, the allele editor window appears, allowing the user to modify its data. These functions work the same way for the electropherogram as well, click on an allele marked in the trace and it becomes blue in the allele table. Double click on the trace and the allele editor window appears. The table contains information about the allele’s number, dye color, the marker range it is included in, the size, the bin left and right ranges, the allele name, and any additional comments.

Figure 54: Electropherogram with allele information in the table below.

Operation and Use Electropherogram Navigation Navigating through the electropherogram is quite simple. The conventions are the same as all of SoftGenetics other applications. Zoom In / Zoom Out: To zoom in on a specific area of interest, left click at the top left corner of desired data and drag the box to the lower right corner of the area. To zoom out, left click anywhere and drag the box from the right to the left. This will restore the original un-zoomed view. Horizontal Movement: To scroll horizontally, hold the right mouse button on any part of the electropherogram and drag the mouse along the trace to the desired location. Marker Modifications To point to a marker, just left click on the vertical marker line. If it is evident that a marker has been selected incorrectly, it can be edited or deleted. To edit or delete a marker, right click on the vertical line. When errant markers are deleted or edited, the specific marker range will automatically resize to encompass all markers that belong to the specific group.

Figure 55: The various components of the sample electropherogram.


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Marker Insertion Likewise, if a user realizes that a specific allele needs to be added to the marker range, the marker can be inserted manually. To inset a marker, right click in the desired allele. A pop up menu will appear. Select Insert from this menu. The allele editor window will appear which allows the user to edit specific information about the marker before it is placed. Then the corresponding marker range will automatically resize to cover the new allele marker.

Figure 56: Addition of Allele Figure 57: Allele Editor Window

Allele Editor

The allele editor allows users to accurately configure or modify an allele marker. If an allele is being inserted, the allele marker initializes the information based on the position of the right mouse click on the electropherogram. If the allele is being edited, the current information pertaining to that marker is initialized. The allele name initially assigned is the allele’s size number, but the user can change the name to anything that is desired. Any pertinent comments may be added. The size can be altered, which automatically repositions the allele on the electropherogram. The bin left and right ranges can be set as necessary. The user can also select which marker range the allele should be included in. It can be one of the existing marker ranges or a new marker range for the allele (s) can be created using the editor.

Moving an Allele Marker To move an allele marker to the center of a desired peak, the user can zoom in on the area, then press and hold the shift key while clicking and holding either mouse button and repositioning the allele marker. Resizing/Moving Marker Range Changing the size of an entire marker range can be done by holding the shift key and clicking and holding either mouse button on the edge of an allele marker range while shrinking or enlarging the entire marker range. The pointer will become a double sided arrow to indicate the resizing will occur. The space ratio between markers is still maintained. To shift an entire marker range, hold the shift key and right click on the center of the name of the range while repositioning.


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Deleting and Modifying a Group of Alleles To delete several alleles at once, hold the control key and draw a box with either mouse button around the alleles that you want to delete. A shaded box will show all the alleles being covered. The user can then right click the shaded box and choose whether to Change Marker, Update Alleles, or Delete Alleles. Selecting Delete Alleles simply deletes the alleles that were covered by the shaded region. Selecting Update Alleles will refresh the information about the alleles in the shaded region. Selecting Change Marker will launch a window titled Edit Group Allele that will allow the user to change the marker range that outlying alleles are grouped in. The user can either select to move the desired alleles to another marker that is already in the sample or enter a new marker range name, which creates a new marker range and include the selected alleles in this range.

Figure 58: Deleting and modifying alleles in a shaded region.

Editing/Deleting a Marker Range To edit or delete an entire marker range, right click on the name of the marker range and select either edit or delete. If delete is selected, a pop up window will appear asking you to confirm deletion. If edit is selected, the Edit Marker window will appear to change the current marker range information. Marker (Range) Editor The Marker Editor allows the user to make modifications to the selected marker range. The title of the selected marker range can be altered, the number if nucleotide repeats can be selected from a drop down box in the range of 1 to 6, and the boundary for the marker range can be set as necessary.

Figure 59: Edit Marker window


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Another way to access the Marker Editor window is to select a particular panel that contains the marker range that you wish to edit in the Available Panel Tree. Just left click the + box next to the desired panel to expand the tree view and find the marker range to edit. Once located, left click the marker range name to select it, and then right click on the selected marker range, which will pop up a menu with the following choices: Edit, Delete, Export and Reload.

Figure 60: Edit alleles though the panel tree. Choosing Edit will show the Marker Editor window shown above and allows the user to change the title, boundaries, and Nucleotide Repeats for the selected marker range. Choosing Delete will allow the user to delete the entire marker range. Choosing reload will cause the software to do a refresh of the marker range. This means that all the allele markers will return to the way the software initially set them. This option will reset any manual changes that the user has made to any allele markers in the range or the range itself.

Editing a Panel To edit an existing panel, select a particular panel that you wish to edit in the Available Panel Tree. Left click on the panel’s name to highlight it, and then right click on the name to show the pop up menu. The choices are to Edit, Delete, and Reload. Selecting Edit will launch the Panel Editor. The Panel Editor allows the user to change the Panel’s Name, choose Ploidy, and decide which base letter is represented by each dye color.

Figure 61: Edit an existing panel through the panel tree.


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The choices for Ploidy range from 1-Monoploid to 10-Decaploid. The drop down boxes for each dye color allow users to choose any base (A, C, G, T) for any of the dye colors. Choosing Delete from the pop up menu will simply delete the entire panel. Choosing Reload from the pop up menu will cause the software to refresh the entire panel with the original marker ranges and allele markers. This will cause any manual user changes to the Panel to be lost.

Figure 62: Edit Panel window with options for Ploidy range and dye color for each base.

Changing Dye Colors Data for each of four specific dyes can be viewed in Panel Editor. To view a new dye color, click the color button, which will be one of the following colors, depending on which dye is currently

being viewed: . This progresses through the dye colors sequentially or a color can be selected from the pull down menu. There are two icons on the Panel Editor toolbar that are helpful in editing panels. The first

icon, Adjust Panel, automatically adjusts allele boundaries to align to the nearest peak. If you use this feature, the software will automatically move all allele markers to the nearest detected peak. This feature will save users time by automating the process of fitting panels to the sample experimental conditions.

The second icon, Check Range in Edit, warns the user if they are attempting to set the left or right range of an allele overlapping with another allele. If checked, this feature will prevent you from setting allele boundaries too close to neighboring alleles.


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Importing and Exporting Panels Once a panel has been created, it may be saved and remain in the Panel Editor, in the list of Panels in the tree. However, you may also wish to save this panel and export it to another location for saving. In order to export the file to an outside location, select Export Panel from the File menu, or right mouse click on the panel to export. After selecting a location, the panel will be saved outside of the software. This file may then be imported back into the software in the future as needed by selecting Import Panel from the File menu. This panel is then added back to the list of available panels in the tree. For MLPA Analysis, we have created many panels for you, based upon the MRC Holland test probe kits (http://www.mrc-holland.com/products.htm). To use SoftGenetics’ MLPA panels:

1. Select Import Panels from the File menu 2. Go to the folder Program Files in the drive the software was saved to 3. Select the folder SoftGenetics 4. Select the folder for the version of the software you are using 5. Select the MLPA Panels folder 6. Select and import the panel you need, as listed by probe name/number 7. After importing these panels, you will need to adjust them to meet your

experimental conditions.

Chapter 5 Fragment Analysis

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Chapter 5 Fragment Analysis Microsatellites are short stretches of repeated DNA found in most genomes that are highly polymorphic in humans and most other species. This variability has made microsatellites a popular genetic marker for genotyping applications such medical genetics, forensics, genetic mapping, and human and plant population studies. They are found in large numbers and are relatively evenly spaced throughout the genome. Due to their small size of 2-6 base pairs, microsatellites can be analyzed using polymerase chain reaction (PCR) and accurately sized using electrophoresis systems.

GeneMarker for fragment analysis is a genotyping tool with an integrated pedigree function. The software is fully automated making analysis quick and easy. GeneMarker automatically corrects for genotyping problems and efficiently analyzes raw fragment data within seconds. GeneMarker also has several printing and output options including an allele report which can be saved as a text file and an integrated pedigree report.

Note: The user must run the data with the correct size standard and panel prior to using the pedigree function (See Chapters 2 and 4).

Chapter 5 Contents Preparation Requirements Check Size Calling Panel Setup Analysis and Functionality Reporting Printing and Saving Pedigree Analysis


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Preparation Requirements For each analysis type, GeneMarker utilizes a unique set of analysis parameters. In the Template Selection dialogue window, be sure to choose the correct Size Standard and Analysis Type as Fragment (Animal) or Fragment (Plant). It is important not to run the samples with a panel until after completing size calling.

Figure 63: Template Selection dialogue box for Fragment The Data Process Options window has many options for auto correction and peak detection thresholds. The suggested thresholds for Diploid Fragment Analysis are 1% for global percentage and 25 % for local percentage. The peak detection intensity threshold is suggested to be 100. The user is advised to leave the stutter peak filter on to 95 % left and 40% right in order for the software to remove stutter peaks within 2.5 bp of each detected allele peak. For Fragment (Polyploidy) the recommended settings are 5 % for global percentage and 15 % for local percentage. The peak detection intensity threshold is suggested to be 100. The user is advised to leave the stutter filter on to 25 % left and 25 % right.

Figure 64: Data Process options for Fragment data analysis. The Additional Settings dialogue window shown in Figure 65 displays the scoring threshold for allele peak detection. The recommended settings for Fragment and Fragment (Plant) data are Reject < 1 Check < 7 Pass. If the user chooses all allele peaks with a score below 1 to be rejected, there is the possibility of a false negative, whereas if scores below 0 are rejected, there is the possibility of a false positive.

Figure 65: Additional Settings window for Fragment data analysis.


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Stutter and Plus A Influence When analyzing animal data sets containing mono-, di-, tri-, tetra-, and penta-nucleotide repeats, we need to set different stutter parameters for each marker. We have used a formula to define the stutter filter for each case.

Nucleotide (n) Stutter Value (s)n Mono-nucleotide 1 s1 = 90%

Di-nucleotide 2 s2 = 81% Tri-nucleotide 3 s3 = 72%

Tetra-nucleotide 4 s4 = 64% Penta-nucleotide 5 s5 = 58%

Plus A is another problem effecting animal Fragment Analysis. The software eliminates Plus A peaks if they are only 1 bp apart and heterozygous. The peak pattern of Plus A is recognized and used to call the alleles where Plus A occurs. When analyzing plant Fragment data the limitations with stutter do not occur. The stutter filter is defined as the % regardless of di-, tri-, and tetra-nucleotide repeats. The Plus A limitation is not considered.

Check Size Calling After running the sample files with the correct size template, it is important to check the accuracy of the size calibration. This can be achieved by accessing the Calibration charts by clicking this icon . In order to obtain meaningful Fragment analysis, it is important to confirm the software’s size calling. Any sample that has been poorly size calibrated can be modified and re-calibrated to improve the matching, or the sample lane may be marked as having failed sizes calibrations. See Chapter 3: Calibration Charts for more information.

Panel Setup It is crucial to create a panel prior to analyzing Fragment data. First run the raw data with the correct Size Standard chosen from the Data Process Options window. Note: Choose None for the Panel. After the raw data has been run with the correct size standard, go to the Tools menu in the toolbar and open the Panel Editor. If the user has previously made a panel appropriate for this data, then it may be imported by selecting Import Panels under the File menu. The panel will be added to the panel tree, displayed at the left of the window. If an appropriate panel does not exist, select Create a New Panel from the File menu and the window shown in Figure 66 will appear. Create a name for the panel and be sure to choose Fragment or Fragment (Plant) for the type of analysis. The recommended method is Automatically Create and Use All Samples. The Panel Editor will then create an accurate panel using data from all the samples.


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Figure 66: Create New Fragment or Fragment (Plant) Panel Window

In the Panel Editor, there is an allele table at the bottom of the active window. In this table, the user may specify the maker name, allele names, designate the left and right boundaries for peak detection (in bp), and add comments. NOTE: Control and Distance only have meaning for MLPA Analysis. Please do not specify these values. It is also possible to shift the peaks slightly to fit the data better. To do this, click on the check mark icon at the top of the page. Additionally, users may utilize the feature Check range in Edit which allows users to modify the marker range, without allowing right and left boundaries to overlap to neighboring allele boundaries.

Figure 67: Allele Table in Panel Editor


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Panel Editor Allele Table Features: 1. Number: Displays the number of alleles called in the panel. 2. Dye: Lists the color of the dye 3. Marker Name: Allows the user to name the marker, such as D1257834. 4. Size: Displays the location (size) of the allele peak in base pairs 5. Left/Right Range: Allows the user to set the boundaries left and right of the control allele location/size in which alleles may be called in samples. This allows peaks that are close to the same location/size to be called. This is specified in base pairs to the left and right. It is possible to change the values in one cell, then right click and choose Set value to column to change all cells. 6. Allele Name: Allows the user to name each allele. Note: it is important to use short names for the alleles so that the names can clearly be read in the electropherogram. For example: “11” means it is an 11 bp repeat, “13.2” means a 13 bp repeat plus 2 base pairs, or also text such as “Y32” 7. Control: Do not use this column. It is only useful in MLPA Analysis. 8. Distance/kb: Do not use this column. It is only useful in MLPA Analysis. 9. Comments: Allows the user to include any comments about each allele in the table. Once the panel has been created, the user may add, edit, or delete allele peaks by right clicking on the allele position in the panel by right mouse clicking on desired sizes in the electropherogram (See Chapter 4). Once the panel has been completed, click the Save icon in the toolbar and exit the Panel Editor. After completion of the panel, it can be exported to another location to be saved and retrieved in the future. To export panels, choose File Export Panel, and select the appropriate location to save the panel for importing in the future.

The user may now run the sized data with the finished panel. Click the green Run arrow

located in the toolbar and re-run the data with the saved panel and size standard. The user is advised to keep the analysis parameters previously chosen in the Data Process Options window and Additional Settings window.


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Graphic Display Following the Data Processing steps, the data is displayed in a number of graphical and report formats.

Figure 68: Fragment Graphic Display After Processing Graphics GeneMarker creates a synthetic gel image from the sample files. This gel image displays the samples across the Y-axis (Ex: #1 corresponds with the first file, etc). The X-axis is the size of the fragment. The user may select any combination of dye colors to view. In addition to the gel image, the software displays the electropherogram trace for each selected sample file. You may also select any combination of dye colors to view in the traces.

Reporting In addition to the graphics, GeneMarker for Fragment displays multiple user-customized

reporting options. In the Allele Table, accessible thru the main toolbar with this icon , you may edit the traces by adding, deleting, confirming, and unconfirming allele calls. After clicking this icon once you will see the sample trace(s) along with their respective allele tables below. After clicking the icon twice, you see only the allele table. Finally, after clicking three times you see only the electropherogram trace again. While in this Allele Table you may use the keys Delete and Shift + Delete (to undelete). By right clicking in the trace or the Allele Table, you can choose to Confirm All and Unconfirm All alleles in the sample trace at one time. A right mouse clicking allows selection of the information columns to be presented in the table.


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Figure 69: Fragment Graphic Display After Processing

To save the Allele Table as a text file, click this icon on the toolbar . In the Fragment Report at the right side of the screen, there are 4 different formats to choose from, with numerous options within each for data presentation. You may choose from: Allele List, Marker Table (Fragment), Bin Table (AFLP/MLPA), and Allele Count. In each report there are options for the orientation (vertically or horizontally) as well as content (all alleles or uncertain calls). For most users, the Marker Table is the best option for Fragment Analysis. When you select a particular dye color or marker to view the trace, allele table and report in, only that information is presented. However, by selecting all colors and markers all alleles may be viewed.

Figure 70: Marker Table Report for Fragment Analysis


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The Report Table may be saved as a text file by clicking on the icon in the Report.

Printing and Saving To Print Fragment Analysis, please click on the icon on the main toolbar. The software offers several printing options (Figure 71). If Selected Samples is chosen, the software will print out the lanes checked in the file manager. Select the information to be printed, choose the lane electropherograms, peak table, or both and the dye colors you wish to print. By checking the Mix Dyes option, a mixture of all the dyes for each chosen sample will be printed on the same page.

Figure 71: Fragment Analysis printing options

Figure 72: Printout for Marker Table Report for Fragment Analysis

The Print Preview page can also be saved as a PDF file by clicking in the Print Preview page. To perform Pedigree Analysis on Fragment data, please see Chapter 6.

Chapter 6 Pedigree Chart

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Chapter 6 Pedigree Chart GeneMarker includes a new tool designed to display and check genotype calls using a pedigree chart. The chart supports multiple generations with remarriages and is directly linked to the corresponding patient electropherograms. Individuals with illogical or abnormal allele calls are outlined in red to facilitate quick and easy genotyping.


Chapter 5 Contents Preparation Requirements Importing and Linking Pedigree (.pre/.ped) Files to Sample Files Opening Pedigree Files Overview Analysis and Functionality Saving and Outputting Pedigree Files


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Preparation Requirements The user must enter either sample files or a previously saved .SGP project file into GeneMarker for Fragment analysis. Once the sample files or project file have been opened in GeneMarker, they must be correctly sized and run with an appropriate panel. After this, the user may then select Applications Pedigree and import a previously created linked pedigree file (*.ped or *.pre) or create a new pedigree file within the software.

Importing and Linking Previously Created Pedigree (.pre/.ped) Files to Sample Files If the user is using a previously created pedigree file, the .ped or .pre file must be linked to the sample files in order to view the sample electropherograms from the pedigree chart. To link a previously created pedigree file with the sample files, go to Tools Pedigree File Name Match. Input the pedigree file into the first panel and the corresponding sample files into the second panel. Specify the character numbers which identify the family name and individual name and then save the PED file. If the filename is 00921_P.1.5001.0001_02.fsa and the family name is 5001 and the individual ID is 0001, then the “Family” Identifier should be from 11 to14 and the “Individual” Identifier should be from 16 to 19. After setting the parameters click the Process button, which will output the linked pedigree file to a GeneMarker specific file (.SMP). The user should then save the .SMP file to the same directory as the original .PED File.

Figure 73: PED File Name Match Tool. Figure 74: Linked Pedigree File Format.


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Opening Pedigree Files Existing Pedigree File After linking the existing pedigree file with the sample files as described in the previous section, the user may open the linked file in the Applications menu Select Pedigree Select Open Pedigree File menu. A dialogue box as shown in Figure 75 will appear. Load the original pedigree file into the top panel and the linked .SMP file should automatically appear in the bottom panel. Click OK and the linked pedigree file will open into a family tree.

Figure 75: Load Linked Pedigree File Dialogue Box New Pedigree File To create a new pedigree file, the user must click on the New Pedigree File icon located in the toolbar. A window as shown in Figure 76 will open allowing the user to enter in the Family Name, Individual Name, Gender, Affect Status. If a sample file exists for the individual, the user can select the individual sample in the Sample File drop down box. Once the first individual has been created, right click on the individual to add the mate and later to add children. Note: It is recommended to begin at the top of the family tree with the oldest generation.

Figure 76: Dialogue box for adding members to a new pedigree file.


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Overview The family tree/pedigree function has a simple page layout. After opening the family tree, the user may either open an existing pedigree file by clicking the Open Pedigree File icon , or create a new pedigree file by clicking on the New Pedigree File icon . The user may choose which family to view from the “Family” drop down box indicated by the red arrow. The family tree is located on the left side of the screen and the sample list and electropherograms are located on the right side of the screen. The user may choose the marker to be displayed from the Marker drop down box or from the color toggle box indicated by the green arrow.

The icon is used to display either individual name or individual ID for each sample. In the image below, the individual IDs are displayed for each sample, which correspond to the individual IDs from the pedigree file and the sample files. The electropherograms that appear at the right are from the mother, father, and highlighted child in the family tree. When the user double clicks on any sample in the family tree, the software will display the electropherograms for that sample’s mother and father, if they have been entered into the software.

Figure 77: Layout of the Pedigree function. Analysis and Functionality Checking Genotype Calls The family tree/pedigree chart is linked to the corresponding sample electropherograms displaying the allele peaks called by the software. Double click on any of the individuals in the family tree, and the electropherogram for that sample along with the electropherograms for his or her parents will appear to the right of the screen. In order for the sample electropherograms to appear, however, it is necessary to input the sample traces or a .SGP file containing the sample traces prior to opening the pedigree chart. If the user creates a new pedigree file after running the data, it is necessary to select the sample files from the drop down box shown in Figure 66 for each individual in the family tree. Individuals without a sample file will appear grayed out in the family tree. Blue Highlighted Node: allele calls are consistent with Mendelian inheritance patterns Red Highlighted Node: an illogical allele call has been found ?? Question Mark at Node: the sample file is empty or lacks a marker due to instrument or PCR problem


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Right click on the individual node to view the marker location of the abnormal allele call. In the example shown in Figure 62, Individual 0010 is highlighted in red due to abnormal allele calls in markers Blue_4, Green_1, and Yellow_5, and has a question mark due to an empty Marker Blue_1. Individual 0010 have alleles detected at positions 198 and 201 and his parents have alleles at positions 201 and 206. The inheritance of allele 206, which appears in father, mother and child, is consistent with Mendelian inheritance patterns, but allele 198, which appears only in the child, is not logical or normal based upon Mendelian inheritance.

Figure 78: Family tree displaying an abnormal allele call based upon Mendelian inheritance.

Correcting Abnormal or Illogical Allele Calls To add, delete, or edit an allele, right click on the allele position in the electropherograms. A window will appear with options to Edit, Add, or Delete an allele. As in the example shown in Figure 79, the allele at position 273 was called as “OL” meaning that the allele was out of the defined bin in the panel. The user may edit such alleles to display the correct size by clicking Edit Allele and enter the size of allele in the panel indicated by the arrow.

Figure 79: Editing abnormal Allele Calls.


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Saving and Outputting Pedigree Files GeneMarker has the capability to save the pedigree files into three different formats

1. Pedigree File (*.Pre or *.Ped) 2. Individual Sample Accordance File

(*.SMP) 3. Loci Description File (*.dat)

Figure 80: Saving Pedigree Files The pedigree and loci description files are common file types used in such pedigree software programs as Merlin and GeneHunter. The Individual Sample Accordance File can be used for importing into GeneMarker’s pedigree tool in the future.

Chapter 7 AFLP Analysis

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Chapter 7 AFLP* Analysis Amplified Fragment Length Polymorphism (AFLP ®) is a polymerase chain reaction (PCR) based genetic fingerprinting technique developed in the early 1990’s by Keygene. AFLP uses restriction enzymes to cut genomic DNA, followed by ligation of complimentary double-stranded adaptors to the ends of the restriction fragments. A subset of the restriction fragments are then amplified using 2 primers complimentary to the adaptor and restriction site fragments. The fragments are visualized on denaturing polyacrylamide gels through either auto radiographic or fluorescence methodologies. GeneMarker® is an efficient, user-friendly software tool designed for the analysis of data generated by AFLP technology. The software is compatible with all electrophoresis systems worldwide, including ABI (Applied BioSystems) files, Megabace files, and SpectruMedix files, as well as slab gel output. The software features high efficiency allele calling, adjustable parameters and various reporting options including a trace comparison report.


Chapter 7 Contents Preparation Requirements Check Size Calling Panel Setup Reporting Printing and Saving *AFLP is a registered trade mark of KeyGene, N.V.


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Preparation Requirements For each analysis type, GeneMarker has unique default parameters. In the Template Selection dialogue window, be sure to choose the correct Size Standard and Analysis Type as AFLP. It is important not to run the samples with a panel until after Size Calling has been completed.

Figure 81: Template Selection dialogue box for AFLP The Data Process Options window shown in Figure 82 has many options for auto correction and peak detection thresholds. The correct settings for AFLP should be a small global percentage plus a slightly larger or equal local percentage. The suggested thresholds for AFLP are 1% for global percentage and 1 % for local percentage. The peak detection intensity threshold is suggested to be 100. The user is advised to leave the stutter peak filter on to 5% left and 5% right in order for the software to remove stutter peaks within 2.5 bp of each detected allele peak.

Figure 82: Data Process options for AFLP data analysis.

The Additional Settings dialogue window shown in Figure 83 displays the scoring threshold for allele peak detection. The recommended settings for AFLP data are Reject < 1 Check < 7 Pass. If the user chooses all allele peaks with a score below 1 to be rejected, there is the possibility of a false negative, whereas if scores below 0 are rejected, there is the possibility of a false positive. The recommended setting for AFLP Unconfidence at Rightside Score is 30. This requires that two peaks to the right of the examined peak must have a score of at least 30 for the peak to be accepted.

Figure 83: Additional Settings window for AFLP data analysis.


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Check Size Calling After running the sample files with the correct size template, it is important to check the accuracy of the size calibration. This can be achieved by accessing the Calibration charts by clicking this icon . In order to obtain meaningful AFLP analysis, it is important to confirm the software’s size calling. Any sample that has been poorly size calibrated can be modified and re-calibrated to improve the matching, or the sample lane may be marked as having failed size calibrations. See Chapter 3: Calibration Charts for more information.

Panel Setup It is crucial to create a panel prior to analyzing AFLP data. First run the raw data with the correct Size Standard chosen from the Data Process Options window. Note: Choose None for the Panel. After the raw data has been run with the correct size standard, go to the Tools menu in the toolbar and open the Panel Editor. If the user has previously made a panel appropriate for this data, then it may be imported by selecting Import Panels under the File menu. The panel will be added to the tree of panels, displayed at the left of the window. If an appropriate panel does not exist, select Create a New Panel from the File menu and the window shown in Figure 84 will appear. Create a name for the panel and be sure to choose AFLP for the type of analysis. The recommended method is Automatically Create and Use All Samples. The Panel Editor will then create an accurate panel using data from all the samples.

Figure 84: Create New AFLP Panel Window In the Panel Editor, there is an allele table at the bottom of the active window. In this table, the user may specify the marker name, allele names, designate the left and right boundaries for peak detection (in bp), and add comments. It is also possible to shift the peaks slightly to fit the data better. To do this, click on the check mark icon at the top of the page. Additionally, users may utilize the feature Check range in Edit which allows users to modify the marker range, without allowing right and left boundaries to overlap to neighboring allele boundaries. NOTE: Do not use the Control and Distance Columns. These are only useful in MLPA Analysis.


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Figure 85: Allele Table in Panel Editor Panel Editor Allele Table Features 1. Number: Displays the number of alleles called in the panel. 2. Dye: Lists the color of the dye 3. Marker Name: Allows the user to name the marker 4. Size: Displays the location (size) of the allele peak in base pairs 5. Left/Right Range: Allows the user to set the boundaries left and right of the control allele location/size in which alleles may be called in samples. This allows peaks that are close to the same location/size to be called. This is specified in base pairs to the left and right. It is possible to change the values in one cell, then right click and choose Set value to column to change all cells. For AFLP the ranges could be set very small in order to allow for alleles only 1 bp apart. 6. Allele Name: Allows the user to name each allele. Note: it is important to use short names for the alleles so that the names can clearly be read in the electropherogram. For example: “Y22”. 7. Control: Do not place anything in this column. It is only used in MLPA. 8. Distance/kb: Do not place anything in this column. It is only used in MLPA. 9. Comments: Allows the user to include any comments about each allele in the table. Once the panel has been created, the user may add, edit, or delete allele peaks by right clicking on the allele position in the panel (See Chapter 4). Once the panel has been completed, click the Save icon in the toolbar and exit the Panel Editor. After completion of the panel, it can be exported to another location to be saved and retrieved in the future. To export panels, choose File Export Panel, and select the appropriate location to save the panel for importing in the future.

The user may now run the sized data with the finished panel. Click the green Run arrow



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Graphic Display Following the Data Processing steps, the data is displayed in a number of graphical and report formats.

Figure 86: AFLP Graphic Display After Processing Graphics GeneMarker creates a synthetic gel image from the sample files. This gel image displays the samples across the Y-axis (Ex: #1 corresponds with the first file, etc). The X-axis is the size of the fragment. The user may select any combination of dye colors to view. In addition to the gel image, the software displays the electropherogram trace for each selected sample file. You may also select any combination of dye colors to view in the traces.


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Reporting Report Tables In addition to the graphics, GeneMarker for AFLP displays multiple user-customized

reporting options. In the Allele Table, accessible on the main toolbar from this icon , you may edit the traces by adding, deleting, confirming, and unconfirming allele calls. After clicking this icon once you will see the sample trace(s) along with their respective allele tables below. After clicking the icon twice, you see only the allele table. Finally, after clicking three times you see only the electropherogram trace again. While in this Allele Table you may use the keys Delete and Shift + Delete (to undelete). By right clicking in the trace or the Allele Table, you can choose to Confirm All and Unconfirm All alleles in the sample trace at one time. By right mouse clicking you may select the information columns to be presented in the table.

Figure 87: AFLP Allele Table Options

In order to save the Allele Table as a text file, please click this icon on the toolbar . In the AFLP Report at the right side of the screen, there are 4 different formats to choose from, with numerous options within each for data presentation. You may choose from: Allele List, Marker Table (Fragment), Bin Table (AFLP/MLPA), and Allele Count. In each report there are options for the orientation (vertically or horizontally) as well as content (all alleles or uncertain calls). For most users, the Bin Table is the best report for AFLP Analysis. When you select a particular dye color or marker to view the trace, allele table and report in, only that information is presented. However, by selecting all colors and markers all alleles may be viewed.


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Figure 88: Bin Table Report for AFLP Analysis

The Report Table may be saved as a text file by clicking on the icon in the Report.

Printing and Saving To Print Fragment Analysis, please click on the icon on the main toolbar. The software offers several printing options (Figure 89). If Selected Samples is chosen, the software will print out the lanes checked in the file manager. Select the information to be printed, choose the lane electropherograms, peak table, or both and the dye colors you wish to print. By checking the Mix Dyes option, a mixture of all the dyes for each chosen sample will be printed on the same page.


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Figure 89: AFLP Analysis printing options

Figure 90: AFLP Analysis Print Preview

Chapter 8 MLPA Analysis

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Chapter 8 MLPA* Analysis GeneMarker® now has the capability to analyze data from Multiplex Ligation-dependent Probe Amplification (MLPA). MLPA is a new technique introduced by the Microbiology Research Center-Holland in January 2002, and has become a rapidly growing technique used in the detection of exon deletions in the genes for BRCA1, MSH2, MLH1, etc., which are associated with breast and colon cancer, as well as trisomies found in Down Syndrome. MLPA is a simple method for simultaneous quantification of up to 45 nucleic acid sequences in a single reaction. With GeneMarker, MLPA data analysis is an efficient, quick, and easy process, with features such as customized reporting, and printing. Chapter 8 Contents Preparation Requirements Check Size Calling Panel Setup Data Normalization Synthetic Control Sample Calculation MLPA Analysis Methods Reporting and Printing MLPA is a registered trademark of MRC, Holland


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Preparation Requirements The data analysis process for MLPA is similar to that of fragment and AFLP data analysis. The analysis parameters are slightly different for MLPA. In the Template Selection dialogue window, be sure to choose the correct Size Standard (GS 500 are common) and Analysis Type is MLPA. It is important not to run the samples with a panel until after completing size calling.

Figure 91: Template Selection dialogue box for MLPA. The Data Process Options window shown in Figure 92 has many options for auto correction and peak detection thresholds. The correct settings for MLPA should be a small global percentage plus a slightly larger or equal local percentage. The suggested thresholds for MLPA are 1% for global percentage and between 5-15 % for local percentage. The peak detection intensity threshold is suggested to be between 70 and 100. The user is advised to leave the stutter peak filter on in order for the software to remove stutter peaks within 2.5 bp of each detected allele peak.

Figure 92: Data Process options for MLPA data analysis. The Additional Settings dialogue window shown in Figure 93 displays the scoring threshold for allele peak detection. The recommended settings for MLPA data are Reject < 1 or 0 Check < Pass. If the user chooses all allele peaks with a score below 1 to be rejected, there is the possibility of a false negative, whereas if scores below 0 are rejected, there is the possibility of a false positive. The MLPA intensity normalization option adjusts the intra lane peak intensities to the same scale for comparative purposes. We recommend Population Normalization. For more explanation about the normalization methods used by GeneMarker, see the MLPA Data Normalization section of this chapter.

Figure 93: Additional Settings window for MLPA data analysis.


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Check Size Calling After running the sample files with the correct size template, it is important to check the accuracy of the size calibration. This can be achieved by accessing the Calibration charts by clicking this icon . In order to obtain meaningful MLPA analysis, it is important to confirm the software’s size calling. Any sample that has been poorly size calibrated can be modified and re-calibrated to improve the matching, or the sample lane may be marked as having failed sizes calibrations. See Chapter 3: Calibration Charts for more information.

Panel Setup It is crucial to create a panel prior to analyzing MLPA data. First run the raw data with the correct Size Standard chosen from the Data Process Options window (Figure 91). Note: Choose None for the Panel. After the raw data has been run with the correct size standard, go to the Tools menu in the toolbar and open the Panel Editor. For MLPA Analysis, we have created many panels for you, based upon the MRC Holland test probe kits (http://www.mrc-holland.com/products.htm). To use SoftGenetics’ MLPA panels:

1. Select Import Panels from the File menu 2. Go to the folder Program Files in the drive the software was saved to 3. Select the folder SoftGenetics 4. Select the folder for the version of the software you are using 5. Select the MLPA Panels folder 6. Select and import the panel you need, as listed by probe name/number 7. After importing these panels, you will need to adjust them to meet your

experimental conditions.

NOTE: If you do not adjust allele markers to fit experimental data, the MLPA Analysis Report and the dosage for mis-matched probes will be “0”. If the user has previously made a panel appropriate for this data, then it may be imported by selecting Import Panels under the File menu. The panel will be added to the tree of panels, displayed at the left of the window. If an appropriate panel does not exist, select Create a New Panel from the File menu and the window shown in Figure 94 will appear. Create a name for the panel and be sure to choose MLPA for the type of analysis. The recommended method is Automatically Create and Use All Samples. The Panel Editor will then create an accurate panel using data from all the samples.


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Figure 94: Create New Panel Window The user must then designate the control probes to be used for data normalization. Double click on the control sample located in the sample list on the left side of the screen and the right click in the control box next to each control probe. Choose Edit Allele and the window shown in Figure 953 will appear. Check the Control Gene box and click OK. Alternatively, in the Allele Table each Control Probe should have a “1” in the column Control.

Figure 95: Designation of Control probes for MLPA Normalization In the Panel Editor, there is an allele table at the bottom of the active window. In this table, the user may specify the marker name, allele names, and locations of the allele from the beginning of the sequence (in kb), designate the left and right boundaries for peak detection (in bp), designate controls and add comments. It is also possible to shift the peaks slightly to fit the data better. To do this, click on the check mark icon at the top of the page. Additionally, users may utilize the feature Check range in Edit which allows users to modify the marker range, without allowing right and left boundaries to overlap to neighboring allele boundaries.


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Figure 96: Panel Editor Panel Editor Allele Table Features 1. Number: Displays the number of alleles called in the panel. 2. Dye: Lists the color of the dye 3. Marker Name: Allows the user to name the marker 4. Size: Displays the location (size) of the allele peak in base pairs 5. Left/Right Range: Allows the user to set the boundaries left and right of the control allele location/size in which alleles may be called in samples. This allows peaks that are close to the same location/size to be called. This is specified in base pairs to the left and right. It is possible to change the values in one cell, then right click and choose Set value to column to change all cells. For MLPA values of approximately 1-1.5 bp would be appropriate left and right ranges. 6. Allele Name: Allows the user to name each allele. Note: A. It is important to use short names for the alleles so that the names can clearly be read in the electropherogram.

B. It is important to give each probe a unique name (Exon 1 and Exon 01, Exon 1 and Ex 1 are appropriate). 7. Control: Set control probes by inputting “1” in this column. 8. Distance/kb: Allows the user to input the distance (in kb) that each allele is from the beginning of the sequence. For example, “38.1” in this column means that the allele of TG_Ex2 is 38.1 kb from the beginning of the sequence of the TGFBR2 gene. 9. Comments: Include any comments about each allele in the table. Once the panel has been created, the user may add, edit, or delete allele peaks by right clicking on the allele position in the panel (See Chapter 4). You may also edit markers by right clicking on the marker name and selecting Edit Marker, Adjust


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Marker, Update Alleles, or Delete Marker (Figure 96). Once the panel has been completed, click the Save icon in the toolbar and exit the Panel Editor. After completion of the panel, it can be exported to another location to be saved and retrieved in the future. To export panels, choose File Export Panel, and select the appropriate location to save the panel for importing in the future. The user may now run the sized data with the finished panel. Click the green Run arrow


Data Normalization Due to the variations of PCR efficiencies from small to large DNA fragments or from sample to sample, two selectable normalization methods are provided. GeneMarker can normalize MLPA-derived data by an internal control probe method1 or a population method. The user is able to specify the normalization method in the Run Wizard prior to analysis. The first normalization method is the traditional method based upon the control probes1. The second method, unique to GeneMarker, normalizes peak intensities based upon the statically most probable median intensities. In order to correct for the peak intensity variation over size, an exponential function a*e-bz is used to fit to the square root of peak intensities, where z is size, and a and b are fitting constants. The normalization using the Control Probes is shown in Figure 97A. This correction removes the trend of dropping intensities as the DNA fragment size increases, and sets the height ratios of control probes to approximately 1. However the trend of peak intensities vary greatly from one sample to another with the internal control probes. We have found that the use of a small number of control probes often results in large errors in the intensity normalization. SoftGenetics’ “Population Normalization” addresses the above problems (Figure 97B). Median peak intensities are derived from the first nine data points, then sliding to data points 2-10, 3-11, etc. to ascertain the local median intensities. Outliers are rejected after applying a median filter. All of the probes (control and test) with the median intensities are then used to fit the exponential function, which results in higher accuracy and lower false positive rates. Both normalization methods take the square root of the intensity ratio and plot the ratios to model a linear regression. The default setting is for the population normalization method, because it usually yields better results.

Figure 97: Comparison of Control Probe (left) and Population (right) normalization.

1 Lampros A. Mavrogiannia, et al., St. James’s University Hospital, Leeds. http://leedsdna.info/science/dosage/REX-MLPA/REX-MLPA_CMGS04.ppt .


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In order to view the normalized data, it is necessary to first have designated the control probes in the Panel Editor and run the data with this panel (See Analysis and Functionality: Panel Editor). The window can be accessed in Applications > MLPA Analysis. The user may then select the correct control sample in the MLPA Analysis box as shown in Figure 98. Displayed Control Sample When either MLPA Ratio or MLPA Regression Analyses are opened, the software has automatically selected a sample to use as the control. While the chosen sample may not actually be the experimental control, this selection is based upon which sample presents the data with the fewest abnormal calls. The user may change the control to reflect their experimental sample or another sample, which they feel portrays the data in a meaningful fashion. It is possible to select another dye color from the pull down menu; the default dye color is blue.

Figure 98: MLPA control sample selection

Synthetic Control Sample Calculation GeneMarker’s MLPA Analysis allows users to create a synthetic control sample that can be used as a control/reference sample. This sample is calculated as the median of all selected sample files. The user may select the sample files that they wish to use to

calculate their control sample, by clicking icon. After selecting the appropriate sample files, please click OK. Select the Synthetic Control Sample from the Control file pull-down menu.

The synthetic sample can be saved as an SCF file by clicking on the toolbar. NOTE: Sample files with a score below the Minimum Lane Score Threshold cannot be used in the control sample calculation.

Control Sample Selection


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Figure 99: MLPA Synthetic Control Sample Calculation

MLPA Analysis Methods GeneMarker features 2 types of MLPA analysis: MLPA Ratio and MLPA Regression. Both MLPA analysis features identify data points that are outliers. Outlying points are determined based upon the deviation of each allele peak relative to the average deviation of all peaks. Any individual peak whose residual deviation is greater than 3 times the average deviation will be considered outlying to the data. These outlying points should be considered possible duplications or deletions need to be reviewed by the user.

Figure 100: MLPA Analysis Settings for Ratio Analysis (left) and for Regression Analysis (right).

In both MLPA Analysis methods, the sample files are given a signal-to-noise type score (0-100) corresponding to the quality of the trace. In the Analysis Settings it is possible to view only samples above a certain score threshold. In order to do this, please set the Minimum Lane Score Threshold to the desired value. All samples below this score will appear in grey rather than in color. In both analysis types, a color-coded triangle at the bottom right corner of each graph depicts the success of the normalization method. A green triangle represents successful normalization (Figure 101, 102); yellow represents normalization that needs to be verified for accuracy, and red means normalization failed for that sample.


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MLPA Ratio Analysis MLPA Ratio plots the ratio of each sample compared to the control. In MLPA Ratio, the ratio of the sample data (blue color) to the control sample (red color) and standardized such that the median point within the data set is considered to be “1”. All other data points are relative to the median value, as depicted in the plots in Figure 101 below. The outlying data points represent duplications and deletions. Duplications will be shown “above” the plotted ratio line and deletions will be “below” the line. When you double click on any point, the dosage histogram and the report also depict this point. The deletion and duplication thresholds may be set in the MLPA Ratio Analysis window (Figure 100).

Figure 101: MLPA Ratio In MLPA Ratio Analysis it is possible to toggle between Population and Control Probe Normalization by right mouse clicking in each sample graph. For some samples Control Probe Normalization may be more accurate, when the control probes and the test probes are in 2 distinct groups (Figure 102).

Figure 102: Control Probe (left) and Population Normalization (right) for a whole gene deletion.


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MLPA Regression Analysis MLPA Regression analysis relies upon a T-Distribution to form the regression line between the square root of the sample and the square root of the control. GeneMarker utilizes an automatic iteration-based regression method. Using this method, the software forms a best-fit line, retains 80% of peaks with smaller deviations and 20% are rejected. GeneMarker then iterates multiple times to reject and retain peaks, with a confidence of 99%. This process is repeated until the regression line has reached the desired confidence. Finally, the removed data points are placed back into the plot, and will show up either on the regression line or as outliers. The parameters can be set in the MLPA Regression Analysis window (Figure 100).

Figure 103: MLPA Regression Plots The MLPA Analysis Settings window can be accessed via Applications MLPA Analysis or by

clicking the icon within the MLPA Analysis windows. These windows feature many user-defined settings that are implemented to identify outliers from the data.

1. Deletion < Normal < Duplication Thresholds: In MPLA Ratio, this allows the user to define the thresholds that determine the ratios below which indicate deletions, and ratios above which indicate duplications.

2. Control Probe Method vs. Population Method Regression, and confidence: In

MLPA Regression, the user may select their preferred normalization method. The Population method is recommended.

3. Minimum T-Distance: In MLPA Regression, this feature helps to reduce false positives

in data that is extremely high in quality, by setting the minimum distance the alleles must be from one another in order to be considered. The recommended setting would be 0.05.


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4. Outlier Filter: In MLPA Regression, this feature allows the user to define the confidence

they would like to have in the software’s calling of outliers. For example: a 99% confidence means that the software is 99% sure that the alleles considered outliers are truly deletions and duplications. Additionally, this feature allows the user to set the percentage of probes that should be used in each iteration of normalization in order to reach the desired confidence. The recommendation is 80%, which means that 20% of the probes will be disregarded before each robust regression line fit.

5. Minimum Dosage Range: In MLPA Regression, this feature helps to reduce false

positives by setting the thresholds that determine the calling of deletions and duplications to desired settings. This is shown as red lines radiating from the origin (0, 0) of the graph. Typical settings would be 0.75 and 1.30.

It is recommended that the Outlier Filter, Minimum T-Distance and Minimum Dosage Range are all used for MLPA Regression Analysis.

Reporting and Printing The reporting options for MLPA data are similar to those for AFLP Analysis. The main allele report shown in Figure 104 can display either the peak intensity for each detected allele or the symbols 1, 0, and?, to represent the presence, absence and questionable presence of alleles. The allele report can be saved as a text file to be printed in Word, Excel, or Notepad. In the MLPA Ratio Report as well as the MLPA Regression Report, the user may select whether duplications, deletions and equivalent data points are displayed. The user may also select whether the peak height, peak height ratio, peak area or probability values are shown in the report.

Figure 104: MLPA Ratio and Regression Report Settings


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Patient Report and Printout The MLPA Patient Printout displays the electropherogram, report, and graph by sample file. It can be saved as a PDF file, as well as printed.

Figure 105: MLPA Clinical Report

Chapter 9 Quantitative Analysis

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Chapter 9 Quantitative Analysis GeneMarker features a new Quantitative Analysis feature to quantify peak area by deconvoluting complex peaks. This function includes two different analysis methods: the Curtain Method and the Deconvolution Method. Users may save the quantified peak area in a report that can be opened in Excel for editing and printing. Chapter 9 Contents Preparation Analysis and Functionality Reporting and Saving


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Preparation Requirements In order to perform Quantification Analysis on data, perform Size Calling first. Following Size Calling, please check the accuracy of the size calling in the Calibration Charts. In order to perform the quantification of the peaks, it is necessary to ensure that the files have been correctly sized. Improve Size Calling for any samples with low scores by adding/deleting and modifying size calls. To open the Quantification Analysis function, go to the Applications menu and select Quantitative Analysis.

Analysis and Functionality After opening the Quantitative Analysis feature, you will need to set the parameters to run

with by clicking on the icon on the toolbar.

Figure 106: Quantitative Analysis Settings window In these windows, you must input the number of peaks you are expecting in this region and specify the number of base pairs between each expected peak. There are 2 analysis methods to choose from: Curtain and Deconvolute. The Curtain method integrates to calculate the area under each individual peak in this region. Therefore, the analysis shows gaps in between the peaks in the region because the region between the peaks is not assigned to one peak or the other for the area calculation. For the Curtain method, the area that between the peaks that is not assigned to either peak is determined based upon the Peak Boundary % peak intensity. This value is set by the user and dictates that in order to be assigned as part of the primary peak, a point along the curve must be at least x % of the primary peak’s intensity.


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It is possible to edit the boundaries of each peak by changing the Peak Boundary % peak intensity, and also to manually edit peak boundaries by holding down the Ctrl key and moving the peak boundary with the mouse. After the new boundary is set as desired, let go of the key and the mouse button and the new area is automatically calculated. This method is best for very complex traces, as it is difficult to calculate the area for a primary peak when secondary peaks exist. Therefore, using this method, you can simply calculate the area for primary peaks and remove the secondary peaks from the calculation by leaving them in the unassigned area between the peak boundaries.

Figure 107: Curtain Method of Quantitative Analysis The Deconvolute method integrates to calculate the area under each peak, but it calculates this value by assigning the region in between the peaks to one peak or the other. This method allows users to view the Individual Peaks (designated in Figure 108 by the red peaks), as well as the Complex Peaks (designated as a black dotted line). The area calculation performed is only for the Individual Peaks, but the Complex Peaks can be shown to give the user a general idea of the Complex Peak shape and distribution. This method is best for very good data with very few, small secondary peaks.

Figure 108: Deconvolute Method of Quantitative Analysis


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You can add, delete and modify peaks to be quantified by right mouse clicking in the

electropherogram. After doing so, you must click the icon to Refresh the data with the user-set changes.

Reporting and Saving The Quantitative Analysis function has a report that lists: sample file name, peak size, peak height, and peak area.

Figure 109: Quantitative Analysis Reporting In addition, this report can be saved in text format to be opened in Excel for editing and printing.

Frequently Asked Questions

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Frequently Asked Questions for GeneMarker 1. General Software Questions 1a. What does GeneMarker do?

GeneMarker is a software program designed for DNA fragment analysis with electrophoresis traces, such as AFLP, Genotyping, STR (Short Tandem Repeat), Snap-Shot, analysis. It is also used for quantification of DNA fragments.

1b. Which instrument data does the software support? GeneMarker software supports most of the data formats from the electrophoresis instruments. The software reads the RSD, ESD and SCF formats used in MegaBace capillary systems from Amersham Biosciences or GE Healthcare; FSA, AB1 and ABI formats used in slab gel or capillary systems from Applied Biosystems; SCF format used in BaseStation Analyzer from MJ Research Inc.; TIF format used in FMBIO imaging systems; SMR and SMD formats in SCE capillary systems from SpectruMedix. 1c. What are the advantages of GeneMarker? The main advantages of the software are ease of use and accurate, quick sample analysis. Automated features of the software include correction of saturated peaks and instrument spikes, removal of pull-ups caused by matrix residue, and baseline subtraction to eliminate noise. The allele calls are done with the pattern recognition algorithms so that false positives are reduced. The majority of functions have been completely automated, using a “smart” software approach to eliminate the need for constant analyst intervention, and to improve analysis to analysis consistency.

2. Software Parameter and Preference Options. 2a. How do I set the parameters for different types of analysis?

Click the icon to begin the Run Wizard and a window titled “Template Selection” will appear. Under “Analysis Type” choose Fragment (default), SnapShot, MLPA or AFLP. To select the “Size Standard” and “Panel” for fragment analysis please see 3a and 3d-3e.

2b. How do I set the analysis parameters for “Standard Color”?

Click the icon to begin the Run Wizard and a window titled “Template Selection” will appear. The default “Standard Color” is red, but if your data uses another color, you may choose the appropriate color (blue, green, yellow, red, orange) from the Standard Color drop-down box. 2c. How do I choose the correct “Size Standard?”

Please see question 3a 2d. How do I choose the correct “Panel?”

For first time users, choose None and run the analysis to perform ‘Size Calling.’ After ‘Size Calling’ is completed, you can either create a new panel (see 3e) or import a panel under File >> Import Panels. To modify an existing panel please see 3d. 2e. How should I set the “Peak Detection Threshold?”

Click the icon to begin the Run Wizard and go to the second window labeled “Data Process-Fragment Analysis.” There are three parameters for peak detection:

1. Intensity: Measurement of the peak height. The recommended setting is 100 (For AFLP analysis it is recommended to lower the threshold). 2. Percentage: Calculates percent of allele peaks to the highest peak in the lane.


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The recommended setting is between 1 and 5. 3. Local Region Percent: Defines the peak detection threshold based upon the percentage of the highest peak in that locus. If the threshold is set to 33% for example, the height of all allele peaks must reach at least 33% of the height of the highest peak in that particular locus. For Fragment and Snapshot analysis, the recommended setting is 30%. For AFLP analysis, the recommended setting is 1%.

2f. How should I set the Stutter Peak Filter (%) threshold?

Click the icon to begin the Run Wizard and go to the second window labeled “Data Process-Fragment Analysis.” The Stutter Peak Filter allows the removal of forward and reverse stutter peaks commonly caused by the chemical reactions. The settings are in % of the primary peak. The default settings will remove stutter peaks that are 90% forward of the primary peak, and 30% following the primary peak (recommended setting). 2g. How do I set the score parameters?

Click the icon to begin the Run Wizard and go to the third window labeled “Additional Settings-Fragment Analysis.” We recommend setting the parameters as follows: the software will reject allelic peaks with a score below 1, check those with a score between 1 and 10, and pass the allele peaks with a score above 10; however, these settings may be adjusted for your preference. Once the analysis has run, the allele report, located on the far right of the screen, will show all of the detected alleles with a particular

symbol. Depending on the previously set parameters, allele peaks with a “ ” symbol

have very low confidence, those with a “ ” symbol fall, within the “check” range and

should be verified, and those represented by the “ ” symbol have high confidence and fall within the “pass” range. The confidence for AFLP peaks can be set. We recommend setting the score to 10, which requires that two peaks to the right of the examined peak must have a score of at least 10 for the peak to be accepted. 2h. How do I view multiple electropherograms at once? Go to View >> Preference and click the Display Settings Tab. The View Settings tab is used to set the precision of the data, in tenths of base pairs, the maximum number of open charts (set to 2), the maximum number of lane electropherograms that can be viewed in one screen, and finally the maximum numbers of Allele label layers.

Range of Options: Peak Size Labeling Sensitivity: 0-2 decimal places Chart Setting Ranges: Max Number of Open Charts: 2 Charts per Screen: 1-8 Allele Labeling Layers: 1-6

3. Template Questions 3a. How do I pick the correct size standard?

In the Run Wizard, please select one size standard that you are using, such as Gene Scan 500, High Definition 400, Internal Lane Standard 600 etc. The software will use this size standard to align all of the lanes. If you don’t know which size standard is used in your experiments, please consult the standard manufacturer or set up your own standard. You may create your own standard by loading the raw data and going to Tools>> Size Template Editor. Choose the size standard that best matches your samples from the Size Standards tree located at the left of the screen.


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You may also import your own size standard or create a new size standard under the File menu. The first time you run the data, click the “Run” icon and select your chosen size

standard i.e. .

3b. How do I create my own size standard in the Size Template Editor? To create a new Size Standard, go to Tools>>Size Template Editor. Then either click the button or click File >> New Size Standard in the toolbar. Name the new Size Standard and then insert size standard peaks where desired by right clicking on that location in the upper panel. The lower panel represents the different samples and you may choose the sample to be displayed by double clicking on the sample name located in the Sample File Tree. A checkmark indicates the sample is displayed in the panel and a blank page indicates it is not displayed:

When you have completed the new Size Standard, go to File >> Save Changes. 3c. What is ‘Size Calling’ and how do I complete it? ‘Size Calling’ is a function which compares the sample files against a selected size standard. ‘Size Calling’ is not necessary to run the Size Template Editor. The Size Template Editor can be run before or after the ‘Size Calling’ is performed, depending on your needs. If your data requires a completely customized size standard, you should not run ‘Size Calling’ first. In this case, the software allows you to create an entirely original size standard for future use through the Size Template Editor. If your project requires a modification to a typical size standard, you can run ’Size Calling’ with the size standard you wish to modify, then use the Size Template Editor to make the necessary changes.

The ‘Size Calling’ function is activated by clicking the green play button in the GeneMarker toolbar. This launches the Run Wizard. The first page is for Template Selection. You must be sure to use the correct size standard for the data and click “Next.” The next page is to specify the data process options that you desire, and then click “Next.” The last page is for additional setting, then click “OK.”

3d. How do I use the Panel Editor?

Prior to using the Panel Editor function, you need to have already started the GeneMarker application and either opened an existing project or opened specific stored data. ‘Size Calling’ must be performed on the data before viewing the data in Panel Editor. Once this is complete, Panel Editor’s complete functionality is available to you. Panel Editor can be accessed by selecting the Tools dropdown from the main GeneMarker page and clicking Panel Editor. If a panel has already been created but needs modifications, you may select the panel you would like to change from the Available Panel Tree and modify the existing panel accordingly. You can decide which files to use in the Sample File Tree. All files with a

check are included in the panel, and files with a page are not selected. The selection or de-selection can be toggled by double clicking on the file or right clicking. Two different electropherogram modes can be toggled in panel manager, ‘Max & Average’ mode and ‘Include All’ mode. The toggle view button can also be used to toggle the Gel Image view in Panel Editor. 3e. How do I create a new panel for my samples? To create a new panel, go to Tools >> Panel Editor. Then either click the button, or


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click File >> Create New Panel in the toolbar. Enter a name for the new panel. You can select the specific panel type desired and method (“Automatic” and “Use All Samples” are suggested). Once the new panel has been created, you view the alleles in three different ways: ‘Max & Average’ mode, ‘Include All’ mode, or gel image. These viewing modes can be toggled

using the icon in the toolbar. If you need to add, delete, or edit an allele, right click on the specific location in the electropherogram or gel image. (For a full description of editing alleles within the Panel Editor see GeneMarker Manual pages 16-18).

4. Answers to Size Calibration Questions 4a. Why do some of my samples fail during data processing?

The Size Calibration function is designed to test the linearity of the size call for each lane. The size call fails when the quality of the sample is very low, because the allele peaks are not detected by the software. As a result, a linear graph cannot be created for samples where the allele peaks are undefined.

4b. How do I correct for samples that failed to match the size standard?

To correct for failed size calling, click the Size Calibration icon . Double click on the failed sample and add alleles to the electropherogram by right clicking on the center of each allele peak. Once you have added the alleles, right click anywhere on the electropherogram and select Update Calibration. Close this page and click the Call Allele

icon . Select Call Allele-All Samples and click “OK.” 5. Answers to Data Report Questions

5a. What does the “ ” symbol mean?

The “ ” symbol means the allele call at that specific position is highly confident and does not need to be verified. You can set the “Pass” parameter within the “Additional Settings” box in the Run Wizard. In this example, allele peaks with a score of 20 of above will pass and be

represented by the “ ” symbol.

5b. What does the “ ” symbol (“OL”) mean?

The “ ” symbol means low confidence for this allele call, out of the possible allele number limit, 3 alleles in diploid species, or unmatched with the panels. “OL”, Off-Ladder, means that the allele call at this position is out of range and therefore undetermined. For example, if a peak has a one or two base pair nucleotide difference from the standard peak, the software


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labels it as “OL,” because the peak needs to be reviewed in the electropherogram for verification You are advised to check the electropherograms for alleles represented by this symbol for confirmation. This number can be set in the “Additional Settings” in the Run Wizard (See 5a).

5c. What does the “ ” symbol mean?

The “ ” symbol is used to represent allele peaks that are within the designated “Check” score range. You may set the allele score check range in the “Additional Settings” box in the Run Wizard (See 5a). Allele peaks within this range will be represented by this symbol and you are advised to verify these peaks in the electropherogram.

5d. How do I save the allele list report?

To save the allele list report, click the Save icon located above the allele report. The allele report will be saved as a text file, so that it can be imported into Excel for printing.

5e. How do I print the allele list report? To print the allele report, save as a text file as described in 4e, and then open in an Excel spreadsheet in a delimited file format. Once you have opened the report in Excel, you can manipulate the columns and rows and print according to your specific needs. 5f. How do I save the peak height information?

To save the peak height information, click the Save Peak Table icon in the toolbar. The peak height information will be saved as a text file, which can be opened and modified using Microsoft Word, Excel, etc. (See Below)

Sample: 2: 05960_PD.009.GH011.5022_PD015_F05_05.fsa Dye Size Height Area Marker Allele Difference Quality Score Blue 116.2 1136 7952 Blue_1 116.2 0.0 Pass 230.0 Blue 120.5 1082 7574 Blue_1 120 0.1 Pass 230.0 Blue 176.3 3861 30888 Blue_5 176.3 0.0 Pass 230.0

Index

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AFLP Analysis Parameters .................................. 60 Allele.................................................................... 84 Allele Call Ranges.................................................. 9 Allele Editor .................................................. 38, 40 Allele Marker Table ............................................. 39 Allele Peak Confidence Score.............................. 10 Allelic ladder........................................................ 10 Analysis Preferences ............................................ 13 Analysis Range ...................................................... 8 Animal Fragment Stutter...................................... 47 AutoRun............................................................... 14 Average Mode...................................................... 35 Base Line................................................................ 8 Binning................................................................. 36 Blue Pedigree Nodes ............................................ 56 Calibration Charts .......................................... 25, 27 Changing Dye Colors........................................... 43 Checking Genotype Calls..................................... 56 Control Probe vs Population ................................ 76 Correcting Abnormal Pedigree Calls ................... 57 Creating Size Standards ....................................... 24 Curtain Quantitative Analysis .............................. 80 Data Entry .............................................................. 6 Deconvolute Quantitative Analysis...................... 80 Deleting / Modifying Alleles by Group ............... 41 Deleting Bins........................................................ 37 Deletion and Duplication Thresholds................... 76 Displayed Control Probe ...................................... 73 Electropherogram Navigation .............................. 39 Electropherogram Viewing .................................. 11 Existing Pedigree Files......................................... 55 Fragment Analysis Parameters............................. 46 Frequently Asked Questions ................................ 83 Importing / Linking Pedigrees.............................. 54 Include All Mode ................................................. 35 Inserting Bins ....................................................... 36 Lane Quality Scoring ........................................... 15 Mark As Failed..................................................... 28 Marker Insertion................................................... 40 Marker Modifications........................................... 39 Marker Range....................................................... 40 Migration Time Correction .................................. 31 Minimum Dosage Range...................................... 77

Minimum T-Distance........................................... 76 MLPA Analysis Methods..................................... 74 MLPA Data Normalization .................................. 72 MLPA Pre-made panels ....................................... 69 Modifying an existing Size Standard ................... 25 Navigation............................................................ 11 Navigation Icons .................................................. 12 Outlier Filter......................................................... 77 Overlay View....................................................... 20 Panel Editor................................................ 7, 32, 33 Panel Manager ..................................................... 85 Panel Tree ...................................................... 34, 85 Peak Boundary % Peak Intensity ......................... 80 Peak Detection Threshold .................................... 10 Peak Marker ......................................................... 28 Peak Saturation ...................................................... 9 Print Report.......................................................... 14 Printing Reports ................................................... 21 Pull-up Removal .................................................... 9 Quality Analysis................................................... 15 Quantitative Analysis........................................... 80 Question Mark at Pedgiree Nodes........................ 56 Red Pedigree Nodes ............................................. 56 Report Viewing.................................................... 11 Reporting ............................................................. 16 Repositioning Peak Markers ................................ 29 Sample File Tree .................................................. 34 Sample Scoring .................................................... 28 Sample Size Alignment........................................ 29 Size Calling Algorithm .......................................... 9 Size Editor............................................................ 24 Size Match ........................................................... 25 Size Standard ....................................................... 23 Size Template Editor........................................ 7, 23 Size Template Manager ....................................... 85 Size/Frame Graphs............................................... 28 Stutter Peak Filter ................................................ 10 Synthetic Control Sample Calculation ................. 73 Trace Comparison................................................ 19 View Preferences Menu ....................................... 12 View Settings ................................................. 13, 84 Wizard................................................................ 5, 8 Zoom In / Zoom Out ................................ 11, 29, 39

Documents

GeneMarker manual 1.4 10 2005c - SoftGenetics · 2017. 12. 21. · Figure 4: Processed Raw Data prior to sizing. Analysis & Setting Program Parameters In the wizard, select the template,