Choose the button-menu command Visualize > Choose a function... > Volcano Plot. 

Hit the button Add to Pipline. 

To display only relevant data we can add a filter and split the data into over- and under-expressed genes by adding additional functions to the pipeline.

Choose the button-menu command Filter > Choose a function... > Filter by statistical significance + Add to Pipeline button

Choose the button-menu command Filter > Choose a function... > Split by log2 fold-change direction + Add to Pipeline button

Hit the button Save Pipeline and close the Pipeline window.

Use the command Pipelines > Apply Pipeline > "Name of the Pipeline" to apply the saved pipeline to a data table. 

-> A series of windows will pop up: 

    - Apply the Pipeline in place ?:  No

    - Choose table: Non-Starvation vs Starvation

    - Choose tables to keep: Select all

    - Save the session

Results: 

- A volcano plot was generated (behind the main window)

- Two more tables were generated - one with over- the other with under-expressed genes.

Where to go from here ? 

The differential analysis scratches just the surface of what RNAlysis can do for you. 

It can handle much more complex experimental situations (see the original tutorial or the complete manual). 

Examples are: 

- Grouping over- and under-expressed genes in several experimental conditions in form of a Venn diagram.

- Checking whether genes with a particular attribute are preferable over- oder under-expressed (enrichment analysis).

- Time series analysis.

- Cluster analysis etc.

If you use it, don't forget to reference the contributors to this software. 

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