Visualizing Data

Golden Helix SVS provides a richly interactive visual interface to present and compare user data.

For information on the custom plotting interface available through Python scripting and the specialized plots shipped with Golden Helix SVS please see Custom Plotting Interface and Specialized Plots.

Types of Plots Available

There are five major non-genomic plot types available in Golden Helix SVS. These include Numeric Value Plot, Histograms, XY Scatter Plots, Linkage Disequilibrium, Heat Maps. These plot types are described below.

Data plotted from a spreadsheet using genomic position as the X-axis (obtained from a genetic marker map) will generate an item in GenomeBrowse. For more information about GenomeBrowse and genomic scale plots see GenomeBrowse: The Genomic Scale Data Visualization Tool.

Uniform Numeric Value Plot

The uniform Numeric Value Plot is a plot of the row label on the X-axis and the value from the column plotted on the Y-axis. Unless a marker map is applied to the spreadsheet, sorting the spreadsheet by a column will result in changing the order the data values are plotted in.

The Numeric Value Plot is used to look for trends associated with a row label or the values for one column.

Histograms

The Histogram is a plot of the frequency of the values in the column plotted. The X-axis is the range of values in the column, and the Y-axis is the frequency of the observations. The number of bins used in the histogram can be changed. Fewer bins will result in higher frequency counts per bin. More bins will result in smaller frequency counts per bin.

The Histogram is used to look for the shape of the distribution of the values in the column plotted.

XY Scatter Plots

The XY Scatter Plot is a plot of one column as an independent variable against one or more columns as dependent variables. The independent variable used for the X-axis and the dependent variable(s) is/are used to define the Y-axis.

The XY Scatter Plot is used to look for relationships between two or more variables.

Uniform LD Plots

The LD plot is a triangular heat map of the LD statistics (D', R^2) between pairs of markers across the genotypic columns in a spreadsheet. The X-axis consists of the active markers from the source spreadsheet. If the markers have a marker map applied the LD plot will be created in GenomeBrowse, see genomicLD. Otherwise the markers will be uniformly spaced (hence the name “Uniform LD”).

If a binary dependent variable is selected, some basic association statistics will be displayed in the Data Console when specific LD points are selected in the graph. Blocks of markers can be created, edited and investigated in a LD plot.

The LD Plot is used to investigate areas of the spreadsheet in strong LD. See Using LD Plots for more information.

Uniform Heat Maps

A Heat Map is an intensity plot of numeric values from a spreadsheet. The X-axis consists of the active markers or columns from the source spreadsheet. The Y-axis consists of sample indexes where the i^{\text{th}} index corresponds to the i^{\text{th}} active sample.

If either the column headers or row labels are genetic markers and have a marker map applied, the heat map will be created in GenomeBrowse, see genomicHeatMap. Otherwise, they will be evenly spaced, and the orientation will be identical to the orientation in the spreadsheet.

A Heat Map is used to investigate areas of the spreadsheet with patterns of intensity or values for multiple samples. See Heat Maps for more information.

Plot Viewer

The Plot Viewer is the viewer and control interface for all types of uniform spreadsheet column plotting in Golden Helix SVS. It can be used to plot any numeric data column from the spreadsheet from which it was launched. A graph is one set of X- and Y-axes on which one or more sets of values are plotted. A graph item is any one set of X- and Y- coordinates plotted on a graph.

Within the same Plot Viewer window you can create one or more graphs each containing one or more items. All graphs share a common X-axis, though the Y-axes for all graphs are independent.

Note

All new instances of the Plot Viewer create a new Navigator Window Node in the Project Navigator.

Opening the Plot Viewer

There are several ways to open the Plot Viewer. Two of which, via the Plot menu or the Tool Bar, open a Parameters dialog to set up the initial parameters for the graphs and plots in the Plot Viewer. The third way, via the column header menu, is a short cut to be used when the user knows exactly which column is to be plotted (or in the case of the XY Scatter Plot, which column is the dependent and which is the independent column). The third approach is most useful when only one graph is desired. Each is described below.

From the Plot Menu

The plot parameters dialog for each of the three types of plots with this dialog can be opened using the Plot menu. Uniform Linkage Disequilibrium (LD) and Heat Map plots can be opened directly from the Plot menu, as these plots do not have a parameters dialog.

Plot Numeric Values on Uniform Scale

To plot numeric values against the row label, select Plot > Numeric Value Plot (Uniform) (see Numeric Value Plot (Uniform) Parameters Window).

numValPlotParams

Numeric Value Plot (Uniform) Parameters Window

The Numeric Value Plot Parameters dialog allows for the selection of multiple Numeric Value Plot to be plotted simultaneously in the same Plot Viewer as the dependent Y-axis and for the initial plot parameters to be set.

The search filter allows the user to search among the column name headers for all numeric columns (real-valued (R),integer-valued (I), or binary (B)). The R/I/B toggle buttons can be deselected or selected to hide or show columns of the specified type. The filter searches all columns of the specified type(s) for the occurrence of the entered string in any part of all column name headers, not necessarily at the beginning of the name. For example, entering the string “-22” in the text box will display up to 1,000 column name headers with “-22” anywhere in the header string. Only 1,000 column name headers are listed at once to maintain the speed and usability of the list.

If there are a small number of columns in the list box either before or after filtering, all columns can be selected by clicking All. All selections can be cleared by clicking Clear.

The item arrangement can also be specified. The choices are:

  • Plot one item per graph
  • Plot all items in one graph

To plot the selected columns with the selected item arrangement, click Plot, to cancel the plot click Cancel.

Plot Histograms

To plot one or more histograms, select Plot > Histograms (see Histogram Parameters Window).

histoParams

Histogram Parameters Window

The Histogram Parameters dialog allows for the selection of multiple numeric columns to be plotted simultaneously as histograms in the same Plot Viewer.

The search filter allows the user to search among the column name headers for all numeric columns (real-valued (R),integer-valued (I), or binary (B)). The R/I/B toggle buttons can be deselected or selected to hide or show columns of the specified type. The filter searches all columns of the specified type(s) for the occurrence of the entered string in any part of all column name headers, not necessarily at the beginning of the name. For example, entering the letter “a” in the text box will display up to 1,000 column name headers with “a” anywhere in the header string. Only 1,000 column name headers are listed at once to maintain the speed and usability of the list.

If there are a small number of columns in the list box either before or after filtering, all columns can be selected by clicking All. All selections can be cleared by clicking Clear.

The item arrangement can also be specified. The choices are:

  • Plot one item per graph
  • Plot all items in one graph

To plot the selected columns with the selected item arrangement, click Plot, to cancel the plot click Cancel.

Plot XY Scatter Plots

To plot one or more XY Scatter Plots using the same independent variable (X-axis), select Plot > XY Scatter Plots (see XY Scatter Parameters Window).

scatterParams

XY Scatter Parameters Window

The XY Scatter Parameters dialog allows for the selection of multiple numeric columns to be plotted simultaneously against one independent variable (or X-axis) as scatter plots in the same Plot Viewer.

This dialog has two search filters, one for the selection of the independent (X-axis) variable and the other for the selection of one or more dependent (Y-axis) variables. Each search filter allows the user to search among the column name headers for all numeric columns (real-valued (R),integer-valued (I), or binary (B)). The R/I/B toggle buttons can be deselected or selected to hide or show columns of the specified type. The filter searches for the occurrence of the entered string in any part of all column name headers for the specified column type(s), not necessarily at the beginning of the name. For example, entering the letter “a” in the text box will display up to 1,000 column name headers with “a” anywhere in the header string. Only 1,000 column name headers are listed at once to maintain the speed and usability of the list of columns.

If there are a small number of columns in the list box for the selection of the dependent variable, either before or after filtering, all columns can be selected by clicking All. All selections can be cleared by clicking Clear.

The item arrangement can also be specified. The choices are:

  • Plot one item per graph
  • Plot all items in one graph

To plot the selected columns with the selected item arrangement, click Plot. To cancel the plot, click Cancel.

Plot Linkage Disequilibrium on Uniform Scale

To plot uniform-scale Linkage Disequilibrium (LD) based on the genotypes in the current spreadsheet, select Plot > Linkage Disequilibrium (Uniform).

Plot a Heat Map on Uniform Scale

To plot a uniform-scale Heat Map based on all active rows and columns, select Plot > Heat Map (Uniform).

From the Tool Bar

Each of the three plot parameter dialogs (Numeric Value, Histogram, XY Scatter Plot) can be opened by selecting the appropriate plot icon in the Spreadsheet Viewer Tool Bar. Uniform LD, and Heat Maps can be created directly by selecting the corresponding icon as long as there is not a marker map applied to the spreadsheet. If there is a marker map, genomic scale LD and Heat Maps will be created by clicking on the plot icons. See genomicLD and genomicHeatMap for more information.

Holding the mouse over one of the plot icons will display a tooltip message indicating the plot type. See From the Plot Menu for more information on the plot types and their parameter dialogs if one exists.

From a Column Header Menu

If a particular column is to be plotted as either a Numeric Value Plot or a Histogram, clicking on the Column Number Header or right-clicking on the Column Name Header will display the Column Header Menu. To plot the column as a Numeric Value Plot, select Plot Variable. To plot the column as a Histogram, select Plot Histogram. Either one of these options will directly open up the Plot Viewer with default plot options.

In order to plot a XY Scatter Plot from the column header menu, at least one column state must be set to dependent. (See Column States for more information on setting column state).

Note

Using this method could create another navigator window node because the state of one or more columns might be changed. Once a column is set as dependent this column will become the Y-axis.

Click on the Column Number Header or right-click on the Column Name Header to get the Column Header Menu for the column that is to be used as the independent variable (X-axis). The XY Scatter Plot option will indicate that the current column will be set as the X-axis. So to plot the one or more dependent columns against this column in XY Scatter Plots, select Plot X:[Column Name Header] vs Y:Dependent(s)

Using the Graph Control Interface

The Graph Control Interface has two components, User Graphs and the Graph and Item settings control boxes.

In general, the node structure consists of User Graphs as the top level node (trunk) where any and all graphs that the user creates are placed under this node, and where new graphs can be created. Next in the hierarchy are Graphs, which are the parent nodes (or branches) and Items are the child nodes (or leaves). If a Graph is selected then the Graph Controls will be visible at the bottom of the Graph Control Interface, but if a graph item is selected then the Item Controls will be visible.

Using the User Graphs Tree Window

The Tree Structure

The User Graphs Tree displays the structure of all graphs and items in each graph. (See Two XY Scatter Plots in a Plot Viewer–Graph Item Filter Tab Visible; the Graph Control Interface is in the black box.) The top levels of the tree correspond to different graphs in the Graph View. From a particular graph, all items in the list under each graph name are the Items. An Item is a column of data or line plotted in a graph. The order of the Items dictates the order in which the points are drawn in the graph. The Item on the top of the list of Items for a graph will be plotted on top of all other graph items. To have an Item on top of all other points in the graph, left-click on the Graph Item name and drag and drop the Graph Item directly below the graph name. In the case of uniform LD plots, an item is the Haplotype Blocks; no other items can be added to LD plots.

graphControlView

Two XY Scatter Plots in a Plot Viewer–Graph Item Filter Tab Visible

To save space, the tree structure for a particular graph can be minimized by clicking the symbol to the left of the graph name hiding the graph. To reshow all graph items, click on the symbol to the left of the graph name. Minimizing a graph in the tree will not change what is displayed in the Graph Viewer.

Add a New Graph

To add a new graph click on the User Graph Tree. This causes the Add Graph to become available in the control panel.

The search filter allows the user to search among the column name headers for all numeric columns (real-valued (R),integer-valued (I), or binary (B)) from the spreadsheet that created the Plot Viewer. The R/I/B toggle buttons can be deselected or selected to hide or show columns of the specified type. The filter searches all columns of the specified type(s) for the occurrence of the entered string in any part of all column name headers, not necessarily at the beginning of the name. For example, entering the letter “a” in the text box will display up to 1,000 column name headers with “a” anywhere in the header string. Only 1,000 column name headers are listed at once to maintain the speed and usability of the list.

Columns cannot be added from other spreadsheets.

Hide a Graph

A graph can be hidden from view without removing its configuration settings. To do this, un-check the box in front of the graph name. This does not remove the graph or its settings from the Plot Viewer, but does remove it from the Graph View. To re-show the graph, check the box in front of the graph’s name.

Rename a Graph Title

To rename a graph, right-click on the graph name and select “Rename”. Renaming the graph node will change the title of the graph, which is displayed when the “Title” option is checked. (See Graph Controls.)

Reordering Graphs

Graphs can be reordered within the User Graphs tree, preserving all Graph settings. To reorder a graph, click on the graph and drag it to the desired location. The effect of reordering graphs in the User Graphs Tree is that the graph is placed below the location where it is dropped.

Multi-select operations are valid for moving graphs. These are: <Ctrl>-left-click selects multiple graphs one at a time, and <Shift>-left-click selects all graphs between the first and last selected graph or item. All selected graphs will be moved to below the specified location from bottom to top of the list of graphs moved.

Delete an Entire Graph

To delete a graph and its associated graph items and remove all its associated settings from the Plot Viewer, right-click on the graph name and select “Delete”.

Multi-select operations are valid for deleting graphs. These are: <Ctrl>-left-click selects multiple graphs one at a time, and <Shift>-left-click selects all graphs between the first and last selected graph or item. All selected graphs will be deleted.

Hide an Item

To hide or prevent drawing of a graph, un-check the box in front of the graph item name. This does not remove the graph item or its settings from the Plot Viewer, but does remove it from the Graph View. To re-show the graph item, check the box in front of the graph item name.

Rename an Item

To rename a graph item, right-click on the graph item name and select “Rename”. Renaming the graph item will also change the name displayed in the legend.

Reordering or Moving Items

Graph Items can be reordered within a graph or moved from one graph to another, preserving all Item settings. To move or reorder an item, click on the item and drag it to the desired location. The effect of reordering items for a graph in the User Graphs Tree is that the item layers are reordered.

Multi-select operations are valid for moving items. These are: <Ctrl>-left-click selects multiple items one at a time, and <Shift>-left-click selects all items between the first item and last selected graph or item. All selected items will be moved to below the specified location. The item that was at the bottom of the item list before selection will be the last item added.

Delete an Item

To delete an item from a graph (which will remove all of its settings from the the Plot Viewer), right-click on the graph item and select “Delete”.

If an item or graph is deleted by mistake, closing the SVS project without saving changes and reopening will revert the project to the last saved state.

Multi-select operations are valid for deleting items. These are: <Ctrl>-left-click selects multiple items one at a time, and <Shift>-left-click selects all items between the first item and last selected graph or item. All selected items will be deleted.

Graph and Item Controls

There are different options and settings for graphs and items. To set the options for a graph, click on the name of the graph for which the settings are to be changed. To set the options for an item, click on the name of that graph item. The options and settings that can be changed for Graphs and Items are listed below.

Multi-select operations are valid for editing graphs or items. These are: <Ctrl>-left-click selects multiple graphs or items one at a time, and <Shift>-left-click selects all graphs or items (of the same type as the first selection) between the first and last selected graph or item. Any options set for all selected graphs or items will be applied to all selected graphs or items.

Graph Controls

Graph controls dictate the general structure of the graph, axes, title, legend, domain and range,, and the addition of any graph items to the graph.

The graph controls are displayed on two tabs. These tabs and their options are displayed below.

  • Graph:

    • Title: Check this box to display the graph title (all plot types).
    • Vertical Flip: Flips an LD plot vertically (only available for LD plots).
    • Overlay: Color for the overlay grid (only available for LD plots).
    • Legend: Check this box to display the graph legend (all plot types except LD).
    • Bin Count Sets the global number of bins for the entire graph. The bins are calculated by taking the minimum and maximum values over all items and subdividing this range by the number of bins specified. (Only available for Histograms.)
    • Row-Min and Row-Max: Specifies the start position row number and the end position row number for zooming in on the X-axis. (Only available for Numeric Value Plot on a uniform scale.)
    • X-Min and X-Max: Specifies the minimum and maximum X-axis values for setting the domain of the plot. (Only available for Histograms or XY Scatter Plots.)
    • Y-Min and Y-Max: Specifies the minimum and maximum Y-axis values for setting the range of the plot. (All plot types except LD.)
    • Marker color: Sets the marker flag color (only available on LD plots.)
    • Data Aggregation Method: Sets the data aggregation method for Heat Maps, choices are color pixels based on the Mean, Min, Max or Extreme value (only available for Heat Maps).
  • Axes:

    • X-Label: Check this box to display the specified X-label (all plot types).
      • Axis: Check this box to display the X-axis. If this box is unchecked then the grid will not be displayed for the x-axis as well (all plot types).
      • Grid: Check this box to display the grid for the X-axis (all plot types).
    • Y-Label: Check this box to display the specified Y-label (all plot types, note label cannot be changed for LD).
      • Axis: Check this box to display the Y-axis (all plot types).
      • Grid: Check this box to display the grid for the Y-axis (all plot types except LD).
  • Add Item: Contains a list of up to the first 1000 few numeric columns in the spreadsheet as well as a line item f(x)=m(x)+b. Checking the box in front of any of these items in the list will create a new graph item in the graph. The settings for these items can be set after adding them to the graph. The search filter can be used to easily select columns by entering a search string. Deselecting or selecting the column type toggle buttons can also help to restrict which columns are shown or searched.

  • Color (LD Plots): Additional colors can be added or removed from the LD intensity scale. Colors can also be changed by clicking on the color buttons. The value for setting the colors can be changed by double clicking on the value.

  • Color (Heat Maps): (Only available for Heat Maps)

    • 2 Color Auto: The minimum and maximum values are calculated for the data visible in the graph. Only the colors can be changed in this mode.
    • 3 Color Auto: The minimum, mean and maximum values are calculated for the data visible in the graph. Only the colors can be changed in this mode.
    • Manual: Additional colors can be added or removed and the values for setting the colors can be changed. CNV Default settings can be selected. The values for the colors can be changed after selecting this option.
  • Group: (Only available for Heat Maps and Variant Maps) The Group control tab enables the user to select a single dimension in which colors can be used to discriminate between complementary data categories. A dimension can be selected by clicking the “Select Variable...” button. An interactive column chooser will pop up, providing a selection of spreadsheet columns to color by. Selecting a numeric column will enable additional control of a threshold value.

    The visualization will update dynamically as the selection of variables and threshold values are modified. Clicking “Close” will hide the column selection control. Clicking “Cancel” will restore the previously saved categories.

  • Filters: (Only available for LD Plots and Heat Maps) A list of available filters is provided via this tab. Existing filters can be selected from the list view, enabling the “Remove” and “Edit..” buttons. Remove will permanently remove a filter from the list. To disable a filter without removing it, use the enable/disable checkbox for that filter. The “Edit...” button will activate an editor to modify the filter. The editor provides a “Cancel” button that restores the previous filter configuration. Clicking the “New Filter...” menu button provides two options: “Dynamic” and “Syntactic”.

    • Dynamic: Adds a new filter to the list of filters and launches a column, logic and parameter selection window. Selecting a column will automatically update the contents of the new filter. If no logic or parameters have been selected, defaults will be assigned and the controls updated to reflect them. Modifications in the dialog will automatically update the filter and the visualization.
    • Syntactic: Adds a new filter to the list of filters and launches a text-based filter definition window. This feature enables the creation of more sophisticated filter logic than is accessible through the “Dynamic” interface. The user must define a logical expression. Filter expressions are applied to each row; thus, column indexes are used to define variables in the expression.
  • Method Options: (Only available for LD)

    • Method: The method consists of two parts, the method and the statistic, the first menu is the method (EM or CHM) and the second is the statistic (R^2 or D^{\prime})
    • Options for EM Method: (Only available when EM method is selected.)
      • Use samples with missings: Indicates whether samples with missing values should be used for the computation.
      • Max Iterations: The maximum number of iterations used for EM computation.
      • Conv Tolerance: Convergence Tolerance for EM method computation.

Item Controls

The Item Controls are displayed on up to three tabs. These tabs and their options are displayed below.

Note

Heat Maps do not have items associated with them and are excluded from the designation of “all plots” for this section.

  • Item: All plots, except histograms and LD, contain the following options and settings:

    • Line: options include the line style, color and weight. If “No Line” is selected from the line type list box, then the other options are grayed out. The line types include:

      • No Line – no line connects the points.
      • Solid – a solid line connects the points to one another.
      • Drop – a line connects the points to the X-axis.
      • Leading Steps – a line connects the points to one another by first stepping up or down and then over to the location of the next point.
      • Mid Steps – a line connects the points to one another by placing the vertical step at the midpoint of the horizontal step. I.e. step half-way horizontally, then the full vertical step, then the remaining half-step horizontally.
      • Trailing Steps – a line connects the points to one another by first stepping right and then up or down to the location of the next point.

      To change the color of a line, select a line, click on the color button and select the desired color. To change the weight of the line, increase or decrease the number in the list box.

    • Symbol: options include the symbol and the color and size of the symbol. If “None” is selected from the symbol list box then the other options are grayed out. There are several different options for symbols. To change the color of a symbol, select a symbol, click on the color button and select the desired color. To change the size of the symbol, increase or decrease the number in the list box.

  • Item: Only Histograms contain the following options and settings:

    • Outline: color selector sets the outline color of the histogram bars, and for the median/mean lines.
    • Fill: color selector sets the fill color of the histogram bars.
    • Opacity: sets the opacity of the histogram. When the slider is all the way to the left, the histogram is completely transparent, all the way to the right and it is completely opaque. Adjusting the opacity is useful when more than one histogram is displayed in a graph and the two histograms overlap.
    • Median: Checking this box shows a line representing the median of the values for the column plotted in the histogram. The color of this line is determined by the outline color.
    • Mean: Checking this box shows a line representing the mean of the values for the column plotted in the histogram. The color of this line is determined by the outline color.
  • Item: Only LD contain the following options and settings:

    • Block Definitions:
      • Load...: Load pre-computed block definitions.
      • Save: Save user defined block definitions to a spreadsheet for later use.
      • Clear All: Clear all blocks from the LD plot.
      • Compute...: Compute haplotype blocks.
    • Tables for Block #: Available if a haplotype block is selected.
      • Haplotype Tables: Outputs various haplotype tables.
      • Subset Markers: Creates a subset spreadsheet based on the markers in a haplotype block.
    • Console Output Option: sets the threshold for displaying haplotypes in the Data Console.
  • Smoothing: All plots, except histograms and LD, contains the following options and settings: Smoothing replaces the Y coordinates with a smoothed valued based on the specified window. The smoothing options are:

    • Mean Smooth, Symmetric
    • Median Smooth, Symmetric
    • Mean Smooth, Asymmetric
    • Median Smooth, Asymmetric

    The window radius value specified for the window indicates the number of points to use for smoothing on either side of the point being smoothed. For example, a window value of 2 replaces each point with a 5 point median or mean value.

    The difference between Symmetric and Asymmetric smoothing is how the boundary cases are handled.

  • Color: All plots (except for LD) contain controls to enable the user to select a single dimension in which colors can be used to discriminate between complementary data categories. A dimension can be selected by clicking the “Select Variable...” button. An interactive column chooser will pop up, providing a selection of spreadsheet columns to color by. Selecting a numeric column will enable additional control of a threshold value.

    The visualization will update dynamically as the selection of variables and threshold values are modified. Clicking “Close” will hide the column selection control. Clicking “Cancel” will restore the previous saved color categories.

    Additionally, this tab enables/disables the operation of the control, as well as provides a list view of the available color categories. Each line in the color category list contains 3 elements: an enable checkbox, a color icon, and category description. Unchecking the checkbox causes the data associated with that category to be hidden, effectively behaving as a filter.

    The “Split” and “Save as filter...” buttons are complex operators that will result in clearing the list in the Color tab, and the creation of new filters in the Filter tab. When clicked, the “Split” button will create new items, and each enabled color category will be assigned to an item. The color of the target item will be set, and a filter corresponding to the category will be added. The “Split” button is only enabled if there are at least 2 enabled color categories. When clicked, the “Save as filter...” button will create a filter from the enabled color categories. The resulting filter represents the data visible when the button was pressed, but without any coloring distinction. The “Save as filter...” button is only enabled when at least one but not all color categories are enabled.

  • Filter: All plots (except for LD) contain options and settings for plotting filtered values. Filtering edits the values displayed in the graph view. As soon as a column to be used for filtering and the filter criteria has been specified, only those values matching the criteria will be displayed. Existing filters can be selected from the list view, and new filters can be added to the list via the “New Filter” button. Options and settings are:

    • New Filter: Two options are provided with this tab is selected, “Dynamic” and “Syntactic.”
      • Dynamic: Adds a new filter to the list of filters and launches a column, logic and parameter selection window. Selecting a column will automatically update the contents of the new filter. If no logic or parameters have been selected, defaults will be assigned and the controls updated to reflect them. Modifications in the dialog will automatically update the filter and the visualization.
      • Syntactic: Adds a new filter to the list of filters and launches a text-based filter definition window. This feature is a technically advanced feature that enables the creation of more sophisticated filter logic than is accessible through the “Dynamic” interface. To be successful, the user must define a logical expression. Filter expressions are applied to each row, thus column indexes are used to define variables in the expression.
    • Edit: Activates an editor to modify the filter. The editor provides a “Cancel” button that restores the previous filter configuration.
    • Remove: Permanently removes a filter from the list. This cannot be undone. To disable a filter without removing it, use the enable/disable checkbox for that filter.

Adding a Line to a Graph

To add a line (other than a vertical line) to a graph, select the graph and in the Graph Options select the Add Item tab. From this tab check the box in front of the f(x)=m(x)+b item in the list box and click Add. This will add by default the line f(x)=x to the graph.

The slope and intercept of the line can be changed by clicking on the graph item created after the line was added. This graph item has only one Graph Item control tab, the Attributes tab. On this tab there are the following controls:

  • Line: Set the color and weight of the line.
  • Slope: Set the slope of the line.
  • Intercept: Set the Y-intercept of the line.

The graph item name will be changed to reflect the current equation of the line, but this graph item can also be renamed by right-clicking on the current graph item name and selecting “Rename”.

Using the Data Console

The Data Console displays information about selected data points or histogram bars in the graph viewer as well as user notes for all graphs in the Plot Viewer. (See Histograms with Data Console Outlined, the Data Console is outlined in black.) The data console is shared by all graphs in the Plot Viewer, not specific graphs.

dataConsole

Histograms with Data Console Outlined

There are three tabs in the Data Console, these tabs are:

  • Current
  • History
  • Notes

Current Tab

This tab displays information on data points or histogram bars selected in the Graph View. Clicking in the graph view will display information on the nearest point (or histogram bar) to the location selected by the mouse. The type of information displayed depends on the type of graph. New information replaces old information and data is not saved when the Plot Viewer closes.

Right-clicking in the Current tab displays the following options:

  • Copy: Copies the selected text to the clipboard.
  • Copy Link Location: Copies the Web URL to the clipboard.
  • Select All: Selects all text in the tab.

Clicking on data in the plot will result in the display of various information about the data and genomic location (if available) in the Current Tab. Value hyperlinks will link to the corresponding cell in the originating spreadsheet.

History Tab

The History tab chronologically lists the information viewed in the Current tab along with the date and time the information was viewed in the Current tab. This information is not saved after closing the Plot Viewer.

Right-clicking in the History tab displays the following options:

  • Clear History: Clears the history tab.
  • Copy: Copies the selected text to the clipboard.
  • Copy Link Location: Copies the Web URL to the clipboard.
  • Select All: Selects all text in the tab.

Notes Tab

This tab saves all information typed in the text box after closing the Plot Viewer. Any information from the Current or History tab can be copied and pasted in this tab to be saved for future instances of the Plot Viewer.

Right-clicking in the Notes tab displays standard text editing options.

Docking, Un-docking or Hiding Plot Viewer Subwindows

The Plot Viewer has subwindows that can be docked, un-docked or hidden to maximize the visibility of the subwindow or the other subwindows. These are the Graph Control Interface, Data Console and Full Domain View.

Un-docking Plot Viewer Items

To un-dock a Plot Viewer subwindow, simply double-click on the Plot Viewer subwindow title bar. This will un-dock the subwindow and pop it out in a new window. This window can be minimized, resized, or maximized like any other window. Minimizing, Maximizing and Restore options are available in a right-click menu on the window title bar.

Docking Plot Viewer Subwindow

All Plot Viewer subwindows are initially docked when the Plot Viewer is opened. To re-dock a Plot Viewer subwindow, double click on the Plot Viewer subwindow title bar. This will cause the window to be re-docked in the default location or the last location it was docked. To dock the Plot Viewer subwindow in a different location, drag the window to the desired location and release the mouse button. The subwindows are only allowed to be docked in a few limited locations.

Hiding Plot Viewer Items

To hide a Plot Viewer subwindow, either click on the X button on the Plot Viewer subwindow title bar, or right-click on the menu or tool bar and select the subwindow to hide. Sub-windows can be re-shown by right-clicking on the menu or tool bar and selecting the subwindow.

Zooming in the Graph View

There are many ways to zoom, they are detailed below.

  1. Zoom by specifying the X and Y dimensions in the Graph Control Interface for a particular graph. Note, changing the X-axis view for one graph changes all other graphs to have the same X-axis.
  2. Zoom in both the X and Y dimensions within the Graph View by left-clicking and dragging to select the new graph dimensions and visible area. After zooming, to view data outside the area chosen but within the same scale use the scroll bars at the right of the graph and at the bottom of the window pane the graph is displayed in.
  3. Zoom in only the X dimension by left-clicking and dragging just below the X-axis. If the X-axis is not shown, then a zoom box will need to be created for both the X and Y dimensions, or through the Graph Control Interface. To view data either to the left or the right of the area chosen, use the scroll bar at the bottom of the window pane the graph is displayed in.
  4. Zoom in only the Y dimension by left-clicking and dragging just to the left of the Y-axis. To view data either above or below the area chosen, use the scroll bar on the right-hand side of the graph.
  5. Zoom in by either x1.5, x3 or x10 times in both dimensions, with a minimum zoom restriction. Right-click and select the desired behavior.
  6. Zoom out by either x1.5, x3 or x10 times in all directions, with the maximum of the initial domain and range of the graph, from a graph that has already been zoomed in. Right-click and select the desired behavior.
  7. Maximize the X-axis zoom to the zoom base, requires the X-axis to have been zoomed in to a region within the zoom base. Right-click and select Maximize X-Axis Zoom.
  8. Maximize the Y-axis zoom to the zoom base, requires the Y-axis to have been zoomed in to a region within the zoom base. Right-click and select Maximize Y-Axis Zoom.

Note

Y-axis zooming is not allowed for LD Plots.

Using LD Plots

Linkage Disequilibrium (LD) is the non-random association of alleles in a population. LD is useful during analysis to identify linkage relationships of interesting markers. LD can be calculated for any spreadsheet with more than one Genotypic type data column. Additionally, the LD visualization provides a means to interactively define haplotype blocks for haplotype association testing (see Haplotype Association Tests).

LD Plot Modes

LD can be visualized with or without marker map data. When marker map data is available GenomeBrowse will launch and draw the LD data in genomic position scaled form, see genomicLD.

Otherwise, the data will be presented in a uniform scale, in the Plot Viewer.

ldPlotCompare

LD in Uniform Scale with Haplotype Blocks

The markers are the individual pentagons along the spine of the LD graph. The width of a marker is determined using the midpoint between a marker and its adjacent markers, thus the exact marker position is always within the marker representation, but may not be centered. Edge markers, however, use symmetry to define the open side and so in those cases the marker is centered within the representation.

Graph Controls Specific to LD Plots

On the Graph tab, the controls specific to LD are:

  • Vertical Flip text
  • Overlay
  • Marker color

The Vertical Flip check box allows for the specification of the location of the spine of the visualization to be either along the top or the bottom of the graph. This control is checked by default, corresponding to the spine at the top of the graph.

The Overlay check box allows for a grid to be drawn over the marker and LD elements. The Overlay is only drawn for markers that are wide enough that drawing the overlay will not obstruct the data. In some position scaled visualizations, there may be some markers that are too wide to draw the overlay, and some that are not. By zooming into a dense region, the marker representations can become large enough to draw the overlay. Unchecking the control will disable this feature entirely.

The Marker color button provides a color chooser for the marker representations.

On the Color tab, color buttons define the colors for the default values of 0.0, 0.5, and 1.0 for Min, Mid, and Max, respectively. These values can be changed by double clicking on the values. Additional splits can be added by clicking the Add button. Splits can be removed by selecting a split and clicking Remove. The minimum number of splits allowed is two. There is no maximum number of splits. Colors for other values are computed by interpolating between the color values selected.

On the Filters tab, a list of available filters is provided. Existing filters can be selected from the list view, enabling the “Remove” and “Edit..” buttons. Remove will permanently remove a filter from the list. To disable a filter without removing it, use the enable/disable checkbox for that filter. The “Edit...” button will activate an editor to modify the filter. The editor provides a “Cancel” button that restores the previous filter configuration. Clicking the “New Filter...” menu button provides two options: “Dynamic” and “Syntactic”. “Dynamic” will add a new filter to the list of filters and launch a column, logic and parameter selection window. Selecting “Syntactic” will add a new filter to the list of filters and launch a text-based filter definition window. This feature enables the creation of more sophisticated filter logic than is accessible through the “Dynamic” interface.

On the Method Options tab, the options for setting LD parameters are available. These options are:

  • Method: The method consists of two parts, the method and the statistic, the first menu is the method (EM or CHM) and the second is the statistic (R^2 or D^{\prime})
  • Options for EM Method: (Only available when EM method is selected.)
    • Use samples with missings: Indicates whether samples with missing values should be used for the computation.
    • Max Iterations: The maximum number of iterations used for EM computation.
    • Conv Tolerance: Convergence Tolerance for EM method computation.

Haplotype Block Sets and LD Graphs

The Haplotype Block Set item is a fixed item of an LD graph, i.e. it cannot be removed, nor can another one be added to the graph. The Block Definitions section of the control panel for blocks presents the following four buttons:

  • Load...
  • Save
  • Clear All
  • Compute...

The Load button launches a spreadsheet selection dialog. A haplotype block definition spreadsheet can then be selected. If the selected spreadsheet contains multiple columns that could be block definitions, an additional dialog will appear for selecting the correct column.

The Save button creates a new spreadsheet from the marker definitions. The button is only enabled if blocks are created of modified manually. If manual changes are made and the save button is not pressed before closing Plot Viewer, a prompt will ask whether the haplotype block changes should be saved or not.

The Clear All button removes all blocks from the graph.

The Compute button activates the Haplotype Block Detection dialog using either all the data available in the plot, or just the data currently visible in the plot. When the dialog’s Run button is pressed, a output spreadsheet will be created as a child of the genetic spreadsheet before it is loaded into the viewer.

Tables for Selected Block

A block can be selected by clicking anywhere within a block on the graph. When a block is selected, the Tables for Block # section will be enabled. The Haplotype Tables button will activate the Haplotype Tables dialog. See Haplotype Tables for more information. Pressing Run will generate spreadsheets in the project navigator as a children of the current Plot Viewer node.

The Subset Markers button performs a column subset of the genetic spreadsheet, where the columns correspond to the markers from the selected block as well as any non-genotypic columns from the original spreadsheet. The output spreadsheet is a child of the genetic spreadsheet.

Frequency Threshold for Console Output

When a block is selected, the application will begin computing haplotype statistics. When the data is ready, it will be presented in the Data Console. To limit the volume of content presented in the console, a haplotype frequency must exceed the Frequency Threshold value. Acceptable values are between 0.00001 and 0.999.

Interactive Block Definition

Haplotype blocks can be created, modified, or deleted via a menu which is accessible by right-clicking on a marker. Create Block ... will be available when clicking on a marker that is not already a member of another block. This action will create a new block with one marker. It will be labeled with the next available number in the block set. A block can be modified by adding or removing markers. Markers adjacent to the edge of the block can be included or excluded by clicking and dragging the vertical line segment of the haplotype block. Markers can be dropped from a block by selecting Remove ... from the menu. Dropped markers from the middle of a block can be added back in by selecting Add ....

The Full Domain View in LD Plots

The Full Domain view for LD graph shows an average value of the LD for adjacent markers. It is not intended as an analytic resource. This view is useful to provide a sense of context while inspecting the graph more closely.

The Data Console in LD Plots

The Data Console provides a detailed text output including hyperlinks when left-clicking on graph elements. There are 3 elements comprising an LD graph:

  • Markers
  • LD Values
  • Blocks Definitions

Left-clicking a marker produces the marker name (linked to the spreadsheet column) and its minor allele frequency.

Clicking an LD value produces the marker information for both markers, including links for each to the spreadsheet columns, the number of markers between the two markers used in the LD computation, computed LD values, and (if available) upper and lower confidence bounds of the computation.

Clicking on a haplotype block unavoidably includes clicking on a marker or an LD value. Clicking will first produce the data for the marker or LD value, followed by block information including the number of markers in the block. Lastly, haplotypes with frequencies above the frequency threshold set in haplotype block control panel are listed in decreasing frequency order.

Haplotype Tables

haploTables

Haplotype Tables Window

When a haplotype block is currently selected:

  • In GenomeBrowse: The Compute Haplotype Tables button is on the Marker Blocks tab.

Clicking this button will launch the Haplotype Tables dialog which allows you to compute various haplotype tables from the set of markers that were defined as a block. The haplotype tables will provide estimates for the probabilities of each haplotype for every sample using a given haplotype estimation method.

At the top of the dialog is a summary of how many markers were selected in the current block. For the purpose of the resulting tables you must define the parameters of the estimation algorithms that are used by the selected tables. See How Haplotype Frequencies are Computed for more details on the haplotype estimation algorithms and their options.

The Per sample EM and Per sample CHM check-boxes produces tables of haplotype frequencies estimated using the EM or CHM algorithm respectively with samples along the rows and haplotypes along the column. Only haplotypes with overall frequencies greater than the frequency threshold will be shown.

A diplotype is a pair of haplotypes from a given sample - one haplotype comes from mom, and the other comes from dad. A sample has one and only one diplotype. However, as with haplotypes, the lack of knowledge of marker phase makes it necessary to estimate the probability a sample has a given diplotype for a given set of markers. The Per sample diplotype check-box creates a diplotype table which presents a list of all probable diplotypes for all samples, where probable is defined by the EM display threshold. If you wish to only display samples whose diplotype probabilities are over, say, 0.8, then set the haplotype frequency threshold to 0.8.

We see in the diplotype table view that often the diplotype can be assigned with very high probability. This table can be output to other data formats for further analysis, or potentially joined with an existing table of response variables, and then the haplotype or diplotype entries can be used as categorical variables to build models of the response in different haplotype or diplotype subpopulations.

Heat Maps

Heat Maps are two-dimensional intensity plots of spreadsheet data. Heat Maps are useful to find non-random patterns in the data, particularly for log ratios or segmentation covariates.

Heat Map Plot Modes

Heat Maps can be visualized with or without marker map data. When marker map data is available GenomeBrowse will launch and draw the Heat Map in genomic position scaled form, see genomicHeatMap.

Otherwise, the data will be presented in a uniform scale, in the Plot Viewer and in the orientation consistent with the generating spreadsheet, i.e. rows will remain rows and columns will remain columns.

heatMap

Heat Map of PCA corrected data

The Y-axis corresponds to the Sample Label. The indices mean the first through n^{th} active rows. The 50^{th} sample index corresponds to the 50^{th} active row or column.

Graph Controls Specific to Heat Maps

The graph controls specific to Heat Maps are:

  • Data Aggregation Method
  • Color

The Data Aggregation Method selection allows for the specification of how pixels are aggregated if there are not enough pixels available to draw all of the data selected. The data needs to be aggregated because in all but a few cases there are more active cells in a spreadsheet than there are available pixels on a computer monitor to display. A decision needs to be made as to what value to show for each pixel. The options available are Mean, Min, Max and Extreme.

  • Mean: Computes the mean value and displays the color based on the overall mean value for the data shown.
  • Min: Displays the color for the pixel based on the minimum value of all data points competing for the pixel.
  • Max: Displays the color for the pixel based on the maximum value of all data points competing for the pixel.
  • Extreme (default): Displays the color for the pixel based on the value that is furthest away from the mean value.

The Color tab allows for selection of the colors used in the intensity gradient as well as the values used for assigning colors. There are three available modes, 2 Color Auto, 3 Color Auto and Manual.

In 2 Color Auto mode, two colors are used for the intensity gradient, and are based on the minimum and maximum values for all data in the current zoom. Changing the zoom will recalculate these values. Only the colors used can be changed in this mode. To change a color, click on the color box and select the desired color.

In 3 Color Auto mode, three colors are used for the intensity gradient, and are based on the minimum, mean and maximum values for all data in the current zoom. Changing the zoom will recalculate these values. Only the colors used can be changed in this mode. To change a color, click on the color box and select the desired color.

In Manual mode, additional color splits can be added or removed. The minimum number of colors allowed is two, and there is no maximum. To change the color, click on the color box and select the desired color. To change the split value, double click on the value and enter in the new value. The colors will be resorted with the smallest value on the top and the largest value on the bottom.

If the Heat Map is being used to look for regions of copy number variation, a helpful option, Set CNV Defaults, is available. This sets four splits with three colors. The split values can be changed to fit specific loss/gain thresholds.

To add a new split click on Add and a copy of the currently selected split will be added to the split list box.

To remove a split, select the split to remove and then click Remove.

To use the minimum, mean or maximum values for a particular zoom for all zooms, change the mode from an auto mode to Manual without changing the values used for splits. Now, no matter what the zoom, the same colors will be used for the same intensities.

The Full Domain View in Heat Maps

The Full Domain view for a Heat Map graph displays the same information as the heat map. It is not intended as an analytic resource. This view is useful to provide a sense of context while inspecting the graph more closely.

The Data Console in Heat Map Graphs

The Data Console provides a detailed text output including hyperlinks when left-clicking on graph elements.

Clicking a Heat Map value produces the row and column information, value, and a link to the spreadsheet cell for the datapoint.

Creating Specialized Plots

The following are instructions for creating common plots in genetic association studies. These are multi-color plots for principal component analysis (PCA) or Gender analysis and Q-Q or P-P Plots.

Multi-Color Scatter Plots for PCA or Gender Analysis

Both of these plots use an XY Scatter Plot and a third categorical column to color the data plotted based on either gender or batch/site/ethnicity information. If there are unexpected results or structure in the plot based on gender or batch/site/ethnicity information, this would indicate that there may be problems with the data.

To create either one of these plots, the appropriate data spreadsheet must be joined with the desired phenotype information. See Joining or Merging Spreadsheets for more information on joining two spreadsheets. Once the spreadsheet is in the correct format, select Plot > XY Scatter Plot. Select the appropriate independent and dependent variables for the particular application. See PCA Analysis or Gender Verification for more information.

Then, in the Plot Viewer, select the graph item listed under the graph. In the Graph Item Controls, select the Color tab. Under Symbol coloring, select By Variable and then the “Select variable...” button. From the list, choose the appropriate gender/population/ethnicity/etc., and click Close.

If you wish to rename the color groups, do so by clicking Split to create Graph Items which can then be renamed.

PCA Analysis

pcaSplitPlot

Plot of Second Eigenvector vs First Eigenvector – Split on Ethnicity

For PCA Analysis the spreadsheet from which the Plot Viewer is launched should be Principal Components joined with the phenotype information. In the XY Scatter Parameters dialog, select the first principal component for the Independent variable and the second principal component for the Dependent variable.

In the Graph Item Control Color tab, select the batch/site/ethnicity/gender phenotype column for coloring (see Plot of Second Eigenvector vs First Eigenvector – Split on Ethnicity).

If there is structure in the plot such that most of the data points corresponding to one batch/site/ethnicity are grouped together, then there is evidence of batch to batch, site to site, or ethnic to ethnic variability and the non-randomness could negatively affect association results. PCA correction using the correct number of principal components will correct for this stratification before analysis.

This process can be repeated for other principal components. When the distribution of the different color data points becomes random, this indicates principal components may be corrected for accurately.

Gender Verification

genderConcord

Gender Verification – Average Y Chr Intensity vs Average X Chr Intensity, Split on Reported Gender

For gender verification the gender phenotype information will need to be joined to the average X intensity and average Y intensity information. The average X and Y intensities will need to be created using a Python script or other means.

Once the spreadsheet is in the correct format, in the XY Scatter Parameters dialog select the average X intensity for the Independent variable and the average Y intensity for the Dependent variable. See Gender Verification – Average Y Chr Intensity vs Average X Chr Intensity, Split on Reported Gender for an example of a gender concordance plot. In this example there are several reported females that exhibit apparent mosaicism, and should be considered for exclusion from the analysis.

In the Graph Item Control Filter tab, select the reported gender phenotype column for splitting.

There should be two clusters of data points, the upper left cluster will correspond to samples with average intensities consistent with male intensities, and the lower right cluster will correspond to samples with average intensities consistent with female intensities. Outliers and data points in the wrong cluster according to reported gender are suspect and should be examined for accuracy or dropped from analysis.

This procedure can be performed if only the X chromosome is available. In this case, sort the Average X Intensity column in Ascending order, and then select Plot > Numeric Value Plot and select the average X intensity for the Dependent variable.

Q-Q Plot or P-P Plot

If “Output Data for P-P/Q-Q Plots” is selected in an analysis window, then columns for plotting this information is output in the association test results spreadsheet.

ppPlot

Plot of Observed versus Expected -Log10 P-Values

A Q-Q Plot is a plot of the observed quantiles versus the expected quantiles. A P-P plot is the observed p-values versus p-value rank or -\log_{10}(p-value) versus -\log_{10}(rank). To plot these values, select Plot > XY Scatter Plot (see Plot of Observed versus Expected -Log10 P-Values). In the XY Scatter Parameter dialog, select the desired expected value as the Independent variable and the respective observed value as the Dependent variable.

In the Plot Viewer, to add a y=x line, click on the graph name in the Graph Control Tree in the Graph Control Interface. From the Graph Controls, select the “Add Item” tab and select the f(x)=m(x)+b item. The default line is the y=x line.

Saving Graphs

Graphs can be exported to several image formats. A convenient Save as PDF option is also available.

When saving a plot, only non-hidden graphs in the plot viewer will appear in the output along with the optional currently visible Full Domain View.

Saving Uniform Graphs to Image Formats

To save a uniform graphs to an image file, select File > Save as Image. This opens the Save as Image dialog which includes a preview of the image that will be saved as well as various options applicable to saving an image. These options are detailed below. See Plot Viewer Save as Image dialog.

If the amount of memory needed to save the data is greater than the specified analysis memory cache size, a warning “Insufficient memory. Increasing the analysis cache size limit may alleviate this problem.” will be displayed. See “Insufficient memory.” Warning for more information.

saveImage1

Plot Viewer Save as Image dialog

  • Preview: A scaled view of the image to be saved is displayed in the Preview window. Larger plots may take longer to draw. The progress of the computation and drawing is shown above the preview. If the progress has not reached 100% before saving, an additional progress dialog will appear. Once the computation has finished the image will be saved. Zoom tools are available below the preview to examine the image more closely.
  • Output File: Select the output file by clicking Browse.... Available image types may include:
    • PNG: Portable Network Graphic
    • BMP: Windows Bitmap
    • JPG: Joint Photographic Experts Group
    • PPM: Portable Pixmap
    • SVG: Scalable Vector Graphic
    • TIF: Tagged Image File Format
    • XBM: X11 Bitmap
    • XPM: X11 Pixmap
  • Image Size: The image size can be changed in pixels by specifying the width and height. If Maintain aspect ratio is checked, changing either dimension results in a proportional change in the other.
  • Margins: The top, bottom, left and right margins (in pixels) can be altered independently by adjusting the appropriate control box.
  • Graph Options:
    • Full domain view: The full domain view is shown at the top of the image. This view can be hidden by unchecking this box. Its minimum size can be adjusted by moving the slider bar. To increase the size of the full domain view, move the slider to the right. To decrease the size of the full domain view, move the slider to the left.

To save the image click Save. To cancel and return to the plot viewer, click Cancel. If an output file has not been selected, a reminder to choose an output file before proceeding will appear.

Saving Uniform Graphs to a PDF

To save graphs to a PDF file, select File > Save as PDF. This opens the Save as PDF dialog which includes a preview of the PDF output that will be saved as well as various options applicable to saving a PDF. These options are detailed below. See Save as PDF dialog.

If the amount of memory needed to save the data is greater than the specified analysis memory cache size, a warning “Insufficient memory. Increasing the analysis cache size limit may alleviate this problem.” will be displayed. See “Insufficient memory.” Warning for more information.

savePDF1

Save as PDF dialog

  • Preview: A scaled view of the output on the selected paper size is displayed in the Preview window. Larger plots may take longer to draw. The progress of the computation and drawing is shown above the preview. If the progress has not reached 100% before saving, an additional progress dialog will appear. Once the computation has finished the PDF will be saved. Zoom tools are available below the preview to examine the output more closely.
  • Output File: Select the output file by clicking Browse....
  • Paper: There are several paper options available. These options are:
    • Unit: The paper size can be specified in various units. The available units are: Inch, Millimeter, Pica, Pixel, and Point. Changing the unit changes the meaning of the paper size and margin values.
    • PPI: (Pixels Per Inch) This value represents pixel density. Increasing this value increases the amount of detail that can be shown on a given page size. The memory required to generate the output increases as the square of the PPI so exercise caution when selecting large PPI values.
    • Page Size: There are several standard paper sizes available to choose from.
    • Width: The width of the paper can be manually set by changing this value. The Page Size will then be set to Custom.
    • Height: The height of the paper can be manually set by changing this value. The Page Size will then be set to Custom.
  • Margins: The top, bottom, left and right margins (in the selected units) can be altered independently by adjusting the appropriate control box.
  • Orientation: The paper orientation can either be set to Portrait or Landscape.
  • Page Range: If there are multiple visible plots in the plot viewer, they may be arranged to span multiple pages. All pages, or a subset can be included in the output. The page range can be specified using hyphens and commas. For example, “1-2,5” results in pages 1, 2 and 5 being included in the output.
  • Graph Options:
    • Maximum graphs per page: The maximum number of graphs can be set by changing this value. There are minimum sizes enforced for graphs, so SVS will try to fit the specified number of graphs on one page, but it may not be possible, in that case the remaining graphs will be moved to additional pages.
    • Full domain view: The full domain view is shown at the top of the image. This view can be hidden by unchecking this box. By default, the full domain view is only shown on the first page, by checking On all pages, the full domain view will be shown at the top of every page. Its minimum size can be adjusted by moving the slider bar. To increase the size of the full domain view, move the slider to the right. To decrease the size of the full domain view, move the slider to the left.

To save the PDF click Save. To cancel and return to the plot viewer, click Cancel. If an output file has not been selected, a reminder to choose an output file before proceeding will appear.

“Insufficient memory.” Warning

If the amount of memory needed to save the data is greater than the specified analysis memory cache size, then this warning will be displayed:

printPrevWarnMess

Insufficient memory warning message when saving data from the plot viewer.

After seeing this warning there are at least four potential actions that can be taken.

  1. Increase the analysis cache size. This will allow more data to be stored in memory allowing for plots with more data points to be saved.

    To increase the analysis cache size, close preview dialog (Save as Image or Save as PDF) and the plot viewer then save and close the project. From the program welcome screen, go to Tools > Global Product Options. On the Application tab, under Memory Usage, increase the Transpose and analysis memory usage value. A reasonable value for this parameter is half of the available RAM for the computer.

  2. Decrease the PPI value. This will require that less data be saved which thus requires less memory.

    To decrease the PPI value, within the Save as PDF Setup dialog, change the specified PPI value to a smaller number if possible.

  3. Decrease the printable area. This will require that less data be saved per inch which thus requires less memory.

    Decrease the printable area...

    • by increasing margins. Change the specified margins to a larger value.
    • by reducing the image size. In Save as Image select a smaller width and height in pixels.
  4. Save regardless of warning. This option will save all the data possible with the current cache sizes. The data saved may not match the data visible in the preview.