Create Track from Experiment

This tool has been deprecated and will be retired in a future version of the software. It has been moved to the Legacy Tools (Image legacy_tools) folder of the Toolbox, and its name has "(legacy)" appended to it. If you have concerns about the future retirement of this tool, please contact QIAGEN Bioinformatics Support team at ts-bioinformatics@qiagen.com.

The Create Track from Experiment tool in the CLC Genomics Workbench enabled the conversion of experiments to tracks.

You can find the Create Track from Experiment tool here:

        Toolbox | Legacy Tools (Image legacy_tool_closed_16_n_p) | Create Track from Experiment (Image create_tracklist_16_n_p).

After you start the tool, you are presented with a wizard where you can choose the experiment that you would like to create a track of. The Create Track from Experiment tool can be run on experiments with associated genomic information, such as those created using expression tracks from the RNA-Seq Analysis tool.

In the case where the experiment has associated genomic information, the Create Track from Experiment tool will automatically infer these and the wizard will jump directly to the filtering step, as shown in figure 35.9.

In the case where the experiment does not have associated genomic information, you will first need to specify how the genomic information should be obtained in the parameters step of the Create Track from Experiment tool (figure 35.8).

Image create_track_from_experiment_parameterstep
Figure 35.8: The "Input parameters" step in the Create Track from Experiment tool.

In the Input parameters step, you must specify the following parameters:

Note! The drop-down menus will only contain the columns that potentially represent the information required by the given parameter. If the experiment does not contain any columns that potentially represent the required genomic information, the drop-down menus may appear empty. In this case, it is not possible to convert the given experiment to a track.

In the filtering step (figure 35.9), you have the following options:

Image create_track_from_experiment_filteringstep
Figure 35.9: The filtering step in the Create Track from Experiment tool.

You can then select in the drop-down menu which analysis you want to use for filtering.

The fold change values are stored as different columns in the experiment, depending on the statistical analysis performed. The Create Track from Experiment tool will automatically use the fold-change column appropriate for the different statistical analyses:

The resulting track will contain only differentially expressed genes whose p-value is lower than the specified threshold and whose fold-enrichment is above the specified threshold.

If the chosen statistical analysis was performed on several pairs of groups, there will be an output track for each tested pair of groups. For example, if the same statistical analysis has been carried out on 'group 1 vs. group 2' and 'group 1 vs. group 3', then the output will contain two tracks, where one is filtered according to the 'group 1 vs. group 2' analysis results and the other one is filtered according to the 'group 1 vs. group 3' analysis results.

When running the Create Track from Experiment tool as part of a workflow, there are a few differences in how the parameters are set (see figure 35.10).

Image create_track_from_experiment_workflow
Figure 35.10: Setting the parameters for the Create Track from Experiment tool in a workflow.

The Create Track from Experiment tool will produce a track or several tracks, if filtering based on analysis results was chosen. The track(s) will contain the following annotations:

Two different view options exist: the Track List and the Table View. When opening the annotated output result, the default view is the Track List. It is possible to open both views in split view by holding down the Ctrl key while clicking on the table icon in the lower left corner of the View Area. The two different views are linked together. This means that when you click once on an entry in the table, the Track List will jump the selected region. With the Zoom to Selection (Image zoom_selection) button it is possible to jump to and zoom in on the selected region (figure 35.11).

The results of any statistical test executed on the experiment, including fold-changes and p-values, can be seen in the tooltip when hovering over each region in the annotation track shown in the Track List (figure 35.12).

Image create_track_from_experiment_divided_view_1_genomics
Figure 35.11: Viewing the track produced by the Create Track from Experiment Tool

Image create_track_from_experiment_divided_view_2_genomics
Figure 35.12: The annotations on the track produced by the Create Track from Experiment Tool