TABLE OF CONTENTS
- 1 Algorithm settings
- 2 Accessing results of the analysis
- 3 Interactive plot page
1 Algorithm settings
1.1 Creating a plot
1.2 Selecting data
In the field "Choose track element", input analyses can be selected. They are listed in the field "Selected analysis results".
1.3 Setting parameters
Once all input analyses have been selected, algorithm parameters can be specified. Ranks obtained from every input analysis can be inverted if down-regulated features are to rank higher (as mentioned above, by default the upregulated features are ranking higher). Next to the interior rank feature you will also be able to manually enter a name for the sub-plot
If an input analysis is of type cluster marker genes or gene association analysis, specific clusters can be selected to be included in the meta-analysis under the field "Select columns". Afterwards, individual selected clusters can be inverted if so desired.
1.4 Running the analysis
Once all parameters have been set, the analysis can be executed by clicking the button "Run" on the top-right of the screen.
2 Accessing results of the analysis
You will be redirected back to the Tracks page where new placeholder ("Rank-based meta analysis") will appear. Click "Select" to view the newly executed analysis.
3 Interactive plot page
3.1 Ranked-based meta-analysis results
By default, the higher the meta-score, the more a feature is upregulated (or more suited in text mining and patent mining), e.g. meta-score of 95 means that the feature is in the top 5% of upregulated features.
For each input analysis, features are first ranked based on results, yielding a ranked lists. From these ranked lists, meta-scores for each analysis are computed (the highest ranking feature gets a meta-score of 100, the lowest ranking 0). Afterwards, meta-scores for every feature are aggregated across all analyses by calculating their product. These aggregated meta-scores are then ranked again and new meta-scores are computed, resulting in a single meta-score for every feature.
3.2 Select input
- In Features to plot, a feature of interest must be selected in order to generate the plot. The selected gene will be carried over to all other plots of the meta-analysis.
- In Datasets to plot, you can choose which of the initial input datasets to plot. These datasets will also be used in recalculating the meta-analysis score.
From the Feature to plot menu all of the features that are detected in all of the input datasets are displayed. It is possible for a feature to be detected only in a subset of all input datasets. If you select such a feature then only the datasets in which that feature is detected will be available in the Datasets to plot menu. If you previously made a selection of datasets and have later selected a feature that is not detected in one of the datasets, that dataset will be automatically dropped from the selection.
Once the input is changed a new plot will be rendered and the meta-score recalculated once the Update plot button is clicked. The input selection will be carried over to all other plots and table of the meta-analysis.
3.3 Plot types
3.3.1 Dot plot
3.3.2 Spider plot
3.3.3 Bar plot
3.3.4 Violin plot
In case you have selected any other type of dataset except the differential analysis while trying to visualize a violin plot the following message will be displayed: "To visualize a violin plot please only select differential analysis results". Once the dataset selection is made the violin plot will render.
3.3.5 String plot
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