Results

In the Results step you can explore your results with dedicated tools and statistical tests. The default screen displays the results for the statistical analysis that is best adapted to your experimental design. But you can create and manage additional analyses.

How to

Discover the Results screen

Analysis tabs

By default, you will see two tabs at the top of the screen:

There will be an additional tab for each newly opened analysis. Clicking a tab will show the results of the corresponding analysis, organized into the following screen areas.

Experimental design view

The experimental design view shows the Experimental design matrix used for your analysis. Its color coding is applied to all other elements on the screen. Note that this view is not available for a Gel analysis.

ExperimentalDesignView

Plot area

The plot area contains one or several plots. When several plots are available, you can click the corresponding tabs to switch between them. Available plots are:

  • Expression profile
  • Interactions plots (one for each factor in a 2-factor analysis)

Display area

The default layout of the images in the Display area corresponds to the layout in the Experimental design matrix. The colors let you easily see what treatment conditions you are looking at. At the right of the Display area, you will find the standard Toolbar to manipulate the image views, and set the visualization options.

ResultsDisplayArea

Results table

The Results table can be found at the bottom of the screen. It summarizes the results for your specific analysis.

Very importantly, the Results table allows you to:

SelectByValuesIcon Filter by values

Click the Filter by values icon to apply various selection criteria to your spots. You could, for instance, select all spots with an ANOVA probability < 0.05 and a maximum Fold change > 2.

AnnotateIcon Annotate

Create and combine spot sets, or annotate spots.

Validate spots

When you systematically review spots (for instance spots sorted in a column, or belonging to a spot set) you can validate the spots. This means that you confirm that a spot is, or is not, of interest. A validation column has a tick box that can be in three states:

  • IncludedBox – The spot is confirmed as being of interest.
  • ExcludedBox – The spots is confirmed as not being of interest.
  • UnvalidatedSpotBox – The spot has not yet been reviewed and validated.

Spots can be validated at two levels:

  • You can validate spots for the current analysis. Do this by using the Analysis-ID column in the results table. Note that although you can display Analysis-ID columns from other analyses in the current results table, you will only be able to edit the Analysis-ID column for the current analysis.
  • You can validate spots for the total experiment. Do this by using the Validation column. Note that you can display the Analysis-ID columns from all analyses in one results table during final review.

Click the Settings icon in the Results table to show or hide validation columns.

Create and manage analyses

The Statistics tab shows the list of your different analyses. By default, there will only be one analysis in the list. Each analysis has its own Analysis-ID, which can be found in the Analysis list, in the name of its tab, and as the validation column (Analysis-ID) of the corresponding Results table.

NewAnalysis

Click New to create an additional analysis. Learn more about the available analysis types:

DeleteAnalysis

To delete an analysis, select it in the analysis list and click Delete.

ViewAnalysis

To view the results of an analysis, select the analysis in the list and click View.

AnalysisProperties

Click Properties to view and edit the Name and Comment of a selected analysis.

Analysis types

Gel analysis

This type of analysis lets you investigate protein expression changes within a set of gels, without taking treatments into consideration.

In the Group table, you can sort and filter spots based on descriptive statistics measures such as Mean, Standard Deviation (SD), Coefficient of Variation (CV) and Range ratio.

You can click the Spot table icon in the Group table toolbar to display the Spot table.

One-factor analysis

This type of analysis lets you find significant protein expression changes between different levels of a single factor. Use the ANOVA probability to evaluate if there is an effect of the factor on the expression of a particular protein spot.

In the Anova table, you can sort and filter spots, for instance based on the p-value for the ANOVA test – indicated Anova (p) – and the maximum Fold change.

You can click the Tables icon to display a number of related tables and views:

  • Spot table – Displays a table with the different spot quantities for each spot in each image.
  • Expression ratio table – Displays a table with the expression ratios for all treatments, relative to a selected reference treatment.
  • Values summary – Displays the quantification value for the selected spot in all images, in the same arrangement as the Experimental design matrix.
  • Anova summary – Displays a detailed output of the ANOVA results.

Two-factor analysis

This type of analysis lets you find significant protein expression changes between different treatments of a two-factor analysis. Use the ANOVA probabilities (3 columns) to evaluate if there is an effect of one of the factors on the expression of a particular protein spot, or if there is a significant interaction between the two factors.

In the Anova table, you can sort and filter spots, for instance based on the different p-values for the ANOVA test – indicated Interaction (p), FactorA (p), FactorB (p) – and the maximum Fold change.

You can click the Tables icon to display a number of related tables and views:

  • Spot table – Displays a table with the different spot quantities for each spot in each image.
  • Expression ratio table – Displays a table with the expression ratios for all treatments, relative to a selected reference treatment.
  • Values summary – Displays the quantification value for the selected spot in all images, in the same arrangement as the Experimental design matrix.
  • Anova summary – Displays a detailed output of the ANOVA results.