GC Image Users' Guide

Peak Detection and Analysis

After correcting the baseline, the separate groups of pixels associated with the separated chemicals can be detected and accurately quantified. In image processing, each such group of pixels is called a blob and the operation of segmenting pixels into blobs is called blob detection. GC Image implements blob detection and various tools for displaying, analyzing, and editing blobs.

Detect Blobs

To detect and quantify blobs in the image, invoke the Detect Blobs operation, either by clicking the Detect Blobs button on the Image Viewer tool bar or selecting Filter -> Detect Blobs from the menu. The blob detection operation takes a brief time (typically no more than a few seconds) and does not change the image.

The blob detection algorithm uses a greedy dilation that successively attaches the largest-valued unassigned pixel to a neighboring blob or forms its own blob if no neighboring peak has been established. Configure -> Configure Settings on the Image Viewer menu bar provides parametric settings for Blob Detection:

Before the algorithm is run, the data values are smoothed to reduce spurious variations associated with noise. The smoothing is considered only during the detection algorithm and no pixel values are actually changed. The widths of the Gaussian blurring filter is configurable. The default width parameters are 0.5 pixels in the first column direction and 2.0 pixels in the second column dimension. The minimum values are 0.0. Larger values tend to produce more errors where two adjacent peaks are detected as a single peak, whereas smaller values tend to produce more errors where a single peak is detected as two separate peaks. If the chemical peaks have many pixels in one or both dimensions of the separation, the corresponding smoothing parameters can be increased.
The blob detection algorithm implements a post-processing filter to eliminate detected blobs that have either a temporal footprint or area (i.e., number of included pixels) that is too small or a maximum peak value that is too small. The default minimum area is 22 pixels and the default minimum peak is 5.0 times the estimated standard deviation of the noise. The minimum value for these configurable parameters is 0.

Figure 1 illustrates the Configure -> Configure Settings -> Blob Detection dialog.

Figure 1: The Blob Detection configuration pane.

The Detect Blobs operation may detect hundreds or even thousands of separate blobs in the image. There are a number of important tasks in analyzing the large volume of blob data.

A user may wish to identify and report on only a fraction of the chemicals in the sample, so one of the tasks of analysis is to designate those blobs that are to be included for reporting.

In a report, the blob data usually should be associated with the name of the chemical that produced the blob and/or the chemical group that produced the blob, so one task of analysis is to identify the blobs by associating chemical names and/or chemical group names with the blobs to be included for reporting.

Calibration of the system and accurate quantification of peaks may require the identification of internal standards (chemicals of known quantity injected into the sample mixture) and the association of sample chemicals with specific internal standards. So, analysis may require the identification of blobs produced by internal standards and the correct associations between sample blobs and internal standard blobs.

Ideally, blobs are well separated and correctly distinguished in the Detect Blobs operation. In practice, imperfections due to noise and small proximity between peaks can lead to detection errors that require editing. For example, one type of error is the splitting of what should be one peak into two blobs and another type of error is the inclusion of what should be more than peak in a single blob. So, another analysis task may be to correct mistakes in the detection of blobs to be included for reporting.

Ideally, blobs are produced by only one chemical peak. In practice, chemicals may co-elute, producing blobs that combine the response to more than one chemical peak. Another analysis task may be to deconvolve or unmix the co-eluted peaks.

The large number of separated chemicals in GCxGC data makes manual analysis tedious and time-consuming, so the automated tools provided by GC Image are essential for efficient processing of large GCxGC data sets. GC Image has tools, described in Identification , that automate much or all of the analysis process. The approach is based on pattern matching: a template that describes the pattern of chemicals peaks in one image is matched automatically to blobs of subsequent images. Similar patterns of blob peaks are seen in runs of similar samples under similar conditions, so templates can be used to make accurate chemical identifications based on previously observed patterns. Then, the chemical names, chemical groups, and internal standard associations in the template are copied automatically to blobs in the target image.

Although GC Image provides a high level of automation, sometimes manual, interactive processing is required. As described below, GC Image allows users to interactively assign chemical names, chemical group names, internal standard associations, reporting status, and other metadata to individual blobs or groups of blobs. Other GC Image tools, also described below, support locally variable blob detection and interactive editing of detected blobs.

Display Blobs

GC Image graphically highlights detected blobs in the Viewport of the Image Viewer, e.g., as shown in Figure 2.

Figure 2: Graphical highlights show the unflagged blobs (outlines in red), included blobs (outlines in light blue), internal standards (outlines in yellow), and associations between included blobs and internal standards (lines in green).

Generic Blob Display configuration settings are accessible via the Configure -> Configure Settings on the Image Viewer menu.

A configuration setting determines whether graphical highlights for blobs are shown in other cursor modes (e.g., graphics mode). The default is to show blob highlights in all modes except template mode.
A configuration setting determines whether graphical highlights are displayed for each of the three classes of blobs:
- Unflagged — blobs that are detected, but neither designated as included nor designated as excluded for reports. (The meanings of inclusion and exclusion are described next.) This is the initial state for all blobs.
- Included — blobs that are designated to be included in reports. Reports are to individually characterize (in the manner appropriate for the type of report) all included blobs.
- Excluded — blobs that are designated as excluded in reports. Reports may include in computations blobs that are not designated as included. Excluded blobs are excluded from such computations. For example, a fractional response report will characterize the fractional response of each included blob to the total responses of all included and unflagged blobs, but will not include excluded blobs in the total.
A configuration setting determines whether the graphical highlighting for each blob is a thin outline, a thick outline, a filled outline, a bounding box, or a bubble. The bubble indicates both retention time (by image location) and volume (by disk size). The default is to highlight with a thin outline.
A configuration setting determines whether or not associations between sample chemicals and associated internal standards are highlighted with a line between the blob peaks. The default is to highlight the internal standard associations with a line.
Configuration settings determine the default colors used for included blobs (default cyan), excluded blobs (default gray), unflagged blobs (default red), internal standard blobs (default orange), internal standard association lines (default green), and selection box (yellow).
Multiple blob display settings can be configured. Then, typing the 't' (or 'T') key while the Image Viewer is active, will cycle through the blob display settings.

Figure 3 illustrates the Configure -> Configure Settings -> Blob Display dialog.

Figure 3: The Blob Display configuration pane.

After blob detection, when the cursor lingers over a blob in the Image Viewer, a tool tip appears with information about the blob. A configuration tab for blob mouse-overs, pictured in Figure 4, determines which blob information is visible in blob mouse-overs. The default mouse-over information configuration is: Blob ID, Compound Name, and Peak Value. At most five fields can be shown in the blob mouse-overs.

Figure 4: The Blob Mouse-Overs configuration pane.

The Text View tool, accessible from the View -> Text View menu option or the tool bar, has a flag for displaying blob assignments at each pixel. This tool provides a quantitative view of each pixel in each blob and is very useful for closely examining blobs.

Selecting Blobs

The Image Viewer palette has four cursor modes for selecting blobs and one mode for drawing a blob:

Point blob selection,
Polyline blob selection,
Rectangle blob selection,
Polygon blob selection, and
Draw blob free hand.
Draw blob with oval tool.
Draw blob with rectangle tool.

The Blob Mode button, located on the Image Viewer palette, shows only the current or most recent blob-selection mode. The Blob Mode can be changed from the pull-down menu that is adjacent to the Blob Mode button. Figure 5 shows the Blob Mode button on the Image Viewer palette.

Figure 5: The cursor modes for blobs are set from a button on the Image Viewer palette.

In point blob-selection mode, a blob is selected by moving the cursor over any pixel inside the border of the blob and clicking the left mouse-button. Once a blob is selected in pixel blob-selection mode, other blobs can be added to the selection set by depressing the control key and clicking of the left mouse-button while the cursor is inside the next blob to be selected. To select from multiple overlapping blobs (e.g., as generated by the Deconvolve/Unmix operation described below), first click the desired location, which will select the overlapping peak with the smallest blob ID. Other overlapping peaks can be selected, in a cycle ordered by blob ID, using the <TAB> key (which deselects the previous peak in the cycle) or the <CTL>+<TAB> keys (which maintains selection of the previous peak in the cycle).

In polyline blob-selection mode, blobs are selected by intersection with a drawn polyline. To draw a polyline, locate the cursor at the starting point of the polyline and click the left mouse-button. Then, similarly locate each successive point of the polyline and click the left mouse-button. At the ending point of the polyline, double-click the left mouse-button. All blobs intersected by the polyline are selected and the polyline disappears. To create a polyline that persists in the image, draw a graphic polyline, as described in Graphics .

In rectangle blob-selection mode, a group of blobs can be selected by moving the cursor to a point above (or below) and left (or right) of the peaks of all blobs to be selected, depressing the left mouse-button, moving the cursor below (or above) and right (or left) of the peaks of all blobs to be selected and releasing the mouse button. All blobs with the peak pixel in the rectangular bounding box are selected and the rectangle disappears. To create a rectangle that persists in the image, draw a graphic rectangle, as described in Graphics .

In polygon blob-selection mode, a group of blobs can be selected by moving the cursor to a point near the blobs to be selected, clicking the left mouse-button, repeatedly moving the cursor around the blobs to be selected and clicking the left mouse-button (drawing a polygon), and double clicking the left mouse-button (to close the polygon). All blobs with the peak pixel in the polygon are selected and the polygon disappears. To create a polygon that persists in the image, draw a graphic polygon, as described in Graphics .

The blob(s) that are selected are highlighted with a colored box. Figure 6 shows a selected blob with a mouse-over that shows information about the blob.

Figure 6: Selected blobs are highlighted by a box.

All blobs may be selected by first setting the cursor mode to Blob Mode and then choosing Edit -> Select All (or clicking in the image and typing the <CTL>+A keys). Three additional tools for selecting blobs by user-specified criteria — Find Blobs, Visualize Blobs, and CLIC tool are described below.

Local Blob Detection

Automated blob detection sometimes fails to correctly detect blobs. For example, detection may fail to identify a blob or detection may split what should be a single blob or detection may join what should be two separate blobs. If blob detection results in many errors, it is best to undo blob detection and try different detection parameters. If only a few blobs are detected incorrectly, it is possible to perform local blob detection on a sub-region or a subset of blobs using different detection parameters. (Alternatively, as described in the next section, a user can manually redraw incorrectly detected blobs.)

In addition to the previously mentioned smoothing and filter parameters, this dialog has a minimum peak reference parameter. The user can choose Relative or Absolute for the algorithm to use when determining if a given peak should be included. Relative will multiply the estimated standard deviation of the noise by the minimum peak value entered. Absolute will only test a given peaks value with the minimum peak value entered. Local blob detection may be performed either in Graphics mode with one graphic selected or in Blob mode with one unexcluded blob selected. Select "Edit -> Local Blob Detection". Then, in the Local Blob Detection dialog, pictured in Figure 7, enter the detection parameters and click "OK". In Graphics mode, all blobs indicated by the graphic are excluded and blob detection is performed on the region. In Blob mode, the selected blob is excluded and local blob detection is performed in its place.

Figure 7: The Local Blob Detection dialog.

Drawing, Excluding, and Editing Blobs

If blob detection fails to correctly detect blobs, a user can manually draw outlines of blobs that were missed, to exclude incorrect blobs (removing them from reporting) and then redraw the outline, or to edit blobs in various other ways. Note that such editing does not change the data, only blob outlines.

One of the blob cursor modes for blobs is Draw Blob mode. In blob draw mode, the user delineates the blob outline in the Viewport by depressing the left mouse-button on the border of the new blob, moving the cursor along the desired outline of the blob, and releasing the cursor at the end of the outline (causing the outline to be closed and all unassigned interior pixels to be assigned to the new blob). If a new blob is drawn to overlap another blob, the pixels in the overlapping region(s) will not be assigned to the new blob unless the blob that is overlapped has been flagged as excluded from reporting or the pre-existing blob value at the pixel is less than the pixel value.

To flag blob(s) as excluded, select the blob(s) to be excluded and then click the Delete / Exclude Object button on the palette. Confirmation for excluding blob(s) is required. A blob that is flagged as excluded will be treated in reporting as if it was not detected, but excluded blobs are maintained in the data, so it is possible to remove the exclusion flag or to examine the data for the presence and history of excluded blobs. Blobs flagged as excluded lose their claim to pixels. For example, suppose that Blob A is flagged as excluded and then Blob B is defined to contain pixels that were contained in Blob A. Then, if the exclusion flag is removed from Blob A, Blob A does not reclaim pixels that now are contained in Blob B.

To facilitate scripting in which blobs are excluded and then redrawn, GC Image supports exclusion of blobs selected by a graphic. So, a user can define a graphic (with optional CLIC function), then select "Edit -> Exclude Blobs in Shape". This operation can be applied without selecting specific blobs, which may be different from image to image, which allows the script to be used without reference to specific blobs.

The Edit Blobs tool, available in the Edit menu in the Image Viewer, is a specialized interface for drawing, excluding, and/or editing blobs. Figure 8 illustrates the Edit Blobs tool.

Figure 8: The Edit Blobs tool allows a variety of actions, including excluding and redrawing blobs.

The first step in using the Edit Blobs tool is to select a blob in the Image Viewer (as described above using one of the blob-selection modes from the palette). Then, select the Edit -> Edit Blobs option from the menu in the Image Viewer .

The Edit Blobs tool resembles the Multi-Projections tool in that it has a sub-image in the upper-left, graphs of slices of rows in the bottom-left, graphs of slices of columns in the upper-right, and a control pane in the lower-right. The sub-image can be shifted by click-and-drag in the sub-image. The Edit Blobs tool can be resized to show a larger or smaller sub-image and the region of interest can be changed by click-and-drag with the right mouse-button. The Reset Display resets the scale to the minimum resolution and the position to center the active blob (or, if no blob is active, the original active blob).

The Edit Blobs tool shows three row and three column slices in one-dimensional graphs below and to the right of the image. The cross-hairs indicate the three row and three column slices in the sub-image that are graphed. The center of the cross-hairs selects the active blob. (If there are overlapping blobs at the cross-hairs, the <TAB> key can be used to cycle the active blob.) The cross-hairs can be relocated in the sub-image by depressing the shift key and clicking the left mouse-button on the desired location. The cross-hairs can be moved incrementally with the four arrow buttons on the Edit Blobs control pane.

The graphs of the one-dimensional slices show the pixel values (in blue), the values of the active blob (in red, with knots), and the values of the other blobs (in black). The values of the active blob can be edited on the row and column slices by moving the graphical knot associated with the blob value up or down. The knots are moved by clicking with the left mouse-button on the knot and dragging it to the desired value. The sum of all blob values at a pixel may not exceed the pixel value.

The Edit Blobs control pane has five additional buttons for editing blobs. There are buttons for splitting the active blob at the center of the cross-hairs either horizontally or vertically along the cross-hair. Pressing these buttons will split the active blob in the specified direction. There is a button for excluding the active blob at the center of the cross-hairs. Pressing this button will flag the active blob as excluded in reporting. There is a button for merging two blobs. After pressing the button to merge blobs, the active blob at the center of the cross-hairs is merged with another blob. The other blob is indicated by pointing the cursor and shift-click with the left mouse-button, then clicking the merge button again to indicate the selection of the other blob is complete. There is a button for drawing a new blob. After pressing this button, locate the cursor on the desired border of the new blob, depress the left mouse-button, move the cursor along the desired outline of the blob (drawing an outline), and release the cursor at the end of the outline (which is closed automatically).

Deconvolve/Unmix Blobs

Although GCxGC has significantly greater separation capacity than conventional GC, chemicals still may co-elute creating blobs consisting of overlapping peaks associated with two or more chemicals. GC Image has a Deconvolve/Unmix tool that can separate overlapping peaks. Like local blob detection, Deconvolve/Unmix has the ability to change how the minimum peak reference is evaluated. Deconvolution refers to processing single channel data (e.g., FID) and unmixing refers to processing for multi-channel data (e.g., MS). The process is the same for both.

The first step is to select one or more blobs in a small region that are presumed to contain two or more chemical peaks.
Next, choose the Edit -> Deconvolve/Unmix option from the menu bar. If the image has a single channel, then the peaks are extracted from the blobs based on a separable peak model with shift-variant peaks. If the image has multiple channels, then the peaks are extracted based on a tri-linear peak model.
When processing completes, a popup dialog asks the user to okay or cancel the operation. The dialog presents an image of the selected blobs and separate images of each extracted peak.

At pixels with overlapping blob peaks, the pixel value will be assigned on a percentage basis to each overlapping peak (with the total percentages no greater than 100%). The Text View tool and the Edit Blobs tools have facilities for presenting the relative assignments of pixel value to multiple peaks.

Separating overlapping peaks is a difficult problem and deconvolution and unmixing processing will not succeed in all cases. The operation works better if:

the overlapping peaks are somewhat separated (e.g., two overlapping peaks detected as two adjacent blobs),
each peak extends over several rows and columns of the data, and
each secondary chromatogram of a peak differs principally in scale (and does not change in shape or retention time).

The Configuration -> Detect Blobs pane has a volume threshold (as a percent of the original volume).

Blob Metadata and Computed Attributes

GC Image maintains computed attributes and metadata about each blob. The computed attributes include maximum peak value, retention times of the peak, etc. The metadata includes:

chemical name,
group name,
constellation name,
whether the blob is to be included or excluded in reporting, and
the internal standard associated with the blob,

None of the metadata values are set during blob detection; all metadata are set with information provided during analysis.

To set the metadata for a blob, it must first be selected. After one or more blobs are selected, a click of the right mouse-button will invoke a popup dialog box for editing the metadata, such as illustrated in Figure 9.

Figure 9: The Blob Metadata popup dialog displays and allows setting of metadata about the blob, including chemical name, group name, etc.

The Blob Metadata popup dialog for a single blob displays the blob's unique ID number and several computed attributes:

ID - a unique identification number assigned by GC Image;
Area - the number of pixels in the blob, i.e., its size irrespective of its values;
Volume - the sum of the values of the pixels in the blob, i.e., the total of its values or total response;
Peak value - the largest value of the pixels in the blob;
Peak location - the coordinate of the peak value in each dimension;
Internal standard - the blob ID of the internal standard (0 if not set);
Volume ratio - the ratio between the volume of the blob and the volume of the associated internal standard.

If a single blob is selected, the popup dialog displays the current values for the chemical name, chemical group name, and constellation name and allows those values to be changed. For a single blob, there are checkboxes to indicate whether or not the blob is to be included in reporting, whether or not the blob is an internal standard, and whether or not the blob is to be excluded in reporting. A blob can be included or excluded, or neither, but not both. A blob that is an internal standard must be included in reporting. There also are flags for creating text labels and/or chemical a structure annotation (as described in Text and Chemical Structure Annotations) based on the chemical name. Finally, there is a Set Color flag. If the flag is set for a blob, the default color (defined for the class) can be overridden with the color chooser.

If multiple blobs are selected, the popup dialog does not display the values specific to individual blobs. If multiple blobs are selected the popup, illustrated in Figure 10, allows setting the chemical group name of all selected blobs, setting the constellation name of all selected blobs, clearing the names of all selected blobs, setting whether or not the selected blobs are to be included in reporting, setting whether or not the selected blobs are internal standards, setting whether or not the selected blobs are to be excluded in reporting, setting whether or not the blobs should have text labels, setting whether or not the blobs should have chemical structure, setting a CLIC expression for all selected blobs and setting a color for all selected blobs.

Figure 10: The Blob Group Metadata popup dialog allows setting of metadata about a selected group of blobs.

The internal standard of a blob that is not itself an internal standard is, by default, set to the nearest blob that is an internal standard. The defaults are applied when blobs are included and when an internal standard is included or excluded. The internal standard of an included blob can be changed by selecting the blob and cycling the association from one internal standard to the next until the correct association is made. Cycle the internal standard by first selecting an included blob (that is not an internal standard) and then clicking the Cycle Internal Standard from the Image Viewer tool bar or selecting Edit -> Cycle Internal Standard from the menu.

Clicking the Clear All Metadata button clears all blob metadata as well as all graphics and text objects. The user must confirm execution of this operation.

Blob Table

GC Image can present metadata and computed attributes for all blobs in an interactive table. Clicking the Show Blob Table button on the Image Viewer tool bar or selecting View -> Blob Table from the menu invokes a sortable table with a row for each detected blob. On each row is that blob's unique ID, metadata, and computed attributes. The blob table has the option to switch between three different tables, blobs, excluded blobs, and areas. The blobs table shows all blobs, except those that have been excluded. Excluded blobs table show only those that have been excluded. The areas table shows the data computed for all areas present in the image. Figure 11 illustrates a portion of an example blob table.

Figure 11: The Blob Table displays information about each blob. The table can be sorted by clicking on a column header.

GC Image supports more than 80 of computed attributes and metadata for blobs. The white paper, GCxGC Blob Metadata and Statistics in GC Image , describes in detail each of the available metadata and computed attributes in GC Image.

Two computed attributes, Amount and Amount Source , reference external files: one file containing a composition table listing constituent compounds and their amounts or concentrations and one file containing a calibration table. The Amount attribute is set either directly from the Amount Table (if the named chemical is listed) or using calibration. The Amount Source attribute describes the method used to determine the Amount attribute value. The references to these external files can be set automatically in GC Project or can be set manually in GC Image using the menu options "Configure -> Configure Amount Table" and "Configure -> Configure Calibration Table". The configuration dialog for the Calibration Table has options for calibration as well as the setting of the external file reference.

The blobs in the table can be sorted in forward or reverse order by clicking on the header of the column to be used as the sort key. (Consecutive clicks reverse the sort order.) Clicking to select a row (or using shift-click to select a range of rows or control-click to select multiple rows) causes the blob(s) selected in the Blob Table to also become selected and highlighted graphically in the Image Viewer. Right-click on a row brings up the metadata dialog for the indicated blob.

The number of decimal digits displayed for floating-point attributes can be set individually. To change the number of decimal digits, click the right button of the mouse on the column header to bring up the precision control dialog. Use the up or down arrows to increase or decrease the number of digits, then click elsewhere to set the indicated number of digits.

Some blob metadata also can be edited directly in the blob table. To edit a field, select the blob in the blob table and click on the field to be edited. Computed values cannot be edited. Metadata fields that can be edited display a text box when clicked. The Compound Name field provides a pull-down menu containing the hit-list returned by MS search.

The blob table columns can be configured via the Configure -> Configure Blob Table on the Image Viewer menu. The Configure Blob Table dialog, pictured in Figure 12, allows the user to add or remove columns from the blob table configuration. Column(s) can be reordered by removing and re-inserting entries in a new position.

Figure 12: The Configure Blob Table allows the user to select the columns of the blob table.

Excluded blobs are not shown in the blob table. However, the blob table pane has a checkbox for toggling between the blob table and the table of excluded blobs.

The blob table can be exported as a text file from the File -> Save Blob Table menu item on the Image Viewer. The exported blob table will contain only the columns specified by the blob table configuration. The blob table is saved as text in comma-separated-values (CSV) format, which can be imported directly in the Microsoft Excel and other data analysis software.

Blob Sets

Blobs sharing the same group name form a blob set. Sets of blobs also are indicated by included graphic objects (points, polylines, rectangles, and polygons). As described in Graphics, graphical objects can be flagged to be included in reporting. Each graphical object that is flagged for inclusion defines a blob set. Point graphics define the set of blobs that contain the point. Polyline graphics define the set of blobs that are intersected. Rectangle and polygon graphics can be used to indicate the set of blobs whose peaks are intersected or contained in the graphic. A graphical object also may have a CLIC expression (described in Chemical Identification ) that imposes rule-based constraints on set inclusion.

GC Image can present information about each blob set in tabular form. Clicking the Show Blob Set Table button on the Image Viewer tool bar or selecting View -> Blob Set Table from the menu invokes a sortable table with a row for each blob set. Figure 13 shows an example blob set table.

Figure 13: The Blob Set Table displays information about blob sets. The table can be sorted by clicking on a column header.

On each row is the blob set's ID (for sets defined by graphics objects), name of the group or defining graphic, number of blobs in the set, number of included blobs in the set, total volume of all blobs in the set, total volume of all included blobs in the set, total fractional response (as percent) of all blobs in the set, and total fractional response (as percent) of all included blobs in the set. Currently, the columns in the blob set table are not configurable.

Each row of the blob set table also has a color selection button. If the color is applied to a blob set, it overrides the color defined for the class (included, excluded, or unflagged) of blobs in the set, but not the colors assigned for specific blobs. The priority for colorizing blobs (from high to low) is blob, group, constellation, graphic(s), and class. If a blob is colorized by its graphic(s) and is contained in multiple sets defined by graphics that apply colors to blobs, then the blob is colored by the average color of those graphics.

The entries in the table can be sorted in forward or reverse order by clicking on the header of the column to be used as the sort key. (Consecutive clicks reverse the sort order.) Clicking to select a row (or using shift-click to select a range of rows or control-click to select multiple rows) causes the blob(s) in selected blob set(s) to become selected and highlighted graphically in the Image Viewer . The number of decimal digits displayed for floating-point attributes can be set individually by clicking the right button of the mouse on a column header, as described for Blob Tables.

The blob set table can be exported as a text file by selecting File -> Save Blob Set Table from the Image Viewer menu. The exported blob set table is saved as text in comma-separated-values (CSV) format, which can be imported directly in the Microsoft Excel and other data analysis software.

Blob Selection and Analysis Tools

GC Image provides three other tools for blob selection: Find Blobs, Visualize Blobs, and CLIC Tool .

The Find Blobs tool, pictured in Figure 14, supports blob selection on the basis of blob ID, compound name, group name, and constellation name. For example, all blobs with a specific group name could be selected en masse. This tool is accessible from the Edit menu.

Figure 14: The Find Blobs tool allows selection of blobs on based metadata.

GC Image provides a Visualize Blobs tool, pictured in Figure 15, for graphing bi-variate relationships between blob statistics and identifying blobs with statistical attributes. For example, the tool can be set to show volume and peak value of each blob. This tool is accessible from the Edit menu.

Figure 15: The Visualize Blobs graphs bi-variate relationships of statistics.

The Visualize Blobs tool is useful for identifying blobs with certain statistical characteristics (e.g., anomalies). The user can draw a polygon in the graphical plane enclosing plotted points of interest, as illustrated in Figure 16, by clicking at each vertex and double-clicking at the final vertex.

Figure 16: The Visualize Blobs with designated blobs enclosed by a polygon.

Then, the user can click the Assign Properties button to bring up the blob group metadata popup, shown in Figure 9 , for setting metadata of the corresponding blobs.

The CLIC Tool supports blob selection using the Computer Language to Identify Chemicals (CLIC) to create powerful rule-based constraints. The CLIC Tool is described in Chemical Identification.

Cluster Blobs

GC Image can separate selected blobs into clusters based on their retention-time proximity — that is, the selected blobs are partitioned so that nearby blobs tend to be placed in the same partition and distant blobs tend to be placed in different partitions. For each cluster, GC Image creates a convex polygon enclosing the inscribing retention-time rectangle of each blob in the cluster. Depending on the configuration and parameterization, the cluster polygons may be included (or not) or added to the template (or not).

To Cluster Blobs, enter Blob mode, select the blobs to be clustered, and select "Edit -> Blob Clustering. Then, in the Cluster Blobs dialog, pictured in Figure 17, choose the clustering algorithm, the scaling of the first-column retention (in pixels) relative to the second-column retention (in pixels), the number of clusters, whether or not to include the cluster polygons, and whether or not to add the cluster polygons to the template.

Figure 17: The Cluster Blobs dialog.

Figure 18 pictures four cluster polygons partitioning selected blobs. If the cluster polygons are included, then the blob set for the cluster will be included in the Blob Set Table. The cluster polygons also can be added automatically to the template. As described in Chemical Identification, if the cluster polygons are added to the template, marker peaks within each cluster also may be determined automatically and added to the template.

Figure 18: Four cluster polygons drawn to partition selected blobs.

Here are the brief descriptions on each clustering algorithm. All blobs are represented by peak locations in pixel coordinates.

K-means: K-means clusters blobs by minimizing the sum-of-squared Euclidean distances from each blob to its cluster center. It is suitable for recovering compact clusters.
Hierarchical clustering algorithms: The hierarchical clustering algorithms, cluster blobs by merging clusters one pair at a time. They start with clusters each with a single blob and keep merging the two closest clusters until the required number of clusters exists. Based on different measures of proximity, there are four algorithms:
- Single linkage: The proximity of two clusters is the minimum distance between two blobs in the two clusters. It tend to generate elongated clusters.
- Complete linkage: The proximity of two clusters is the maximum distance between two blobs in the two clusters. It tends to generate compact clusters.
- Average group linkage: The proximity of two clusters is the average distance between two blobs in the two clusters. It is a compromise between single linkage and complete linkage.
- Complete linkage with PCA: The proximity of two clusters is the determinant of covariance matrix of the union of the two clusters in their PC (principal component) space, whose square root is proportional to the area or volume generated by the data. It tends to find natural clusters.

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