To run the ready-to-use workflow:
Toolbox | Ready-to-Use Workflows | Whole Transcriptome Sequencing () | Human, Mouse or Rat | Identify and Annotate Differentially Expressed Genes and Pathways ()
- Double-click on the Identify and Annotate Differentially Expressed Genes and Pathways ready-to-use workflow to start the analysis. If you are connected to a server, you will first be asked where you would like to run the analysis.
- Next, you will be asked to select the samples to analyze (figure 18.28). You can select several GE tracks or TE tracks generated by the RNA-Seq analysis tool, but not a combination of both. Click Next.
- In the next wizard step you can set up the experimental design associated with the data (figure 18.29):
- Choose the metadata table that was associated to the GE or TE tracks used in the previous step.
- Choose the factor (must be one of the metadata category) that should be used to test for differential expression.
- It is possible to specify confounding factors, i.e., factors that are not of primary interest, but may affect gene expression.
- The Comparisons panel determines the number and type of statistical comparison tracks output by the workflow (see Output of the Differential Expression for RNA-Seq tool for more details).
- In the next step you can choose to preview the settings and save the results (see figure 18.30).
Click Finish to start the analysis.
The following outputs are generated:
- PCA for RNA-Seq plot () Projects a high-dimensional dataset (where the number of dimensions equals the number of genes or transcripts) onto two or three dimensions.
- Statistical Comparison () The information can be accessed in two different ways:
- Open as a track, hold shift and hover over a feature. A tooltip will appear with information about gene name, results of statistical tests, and expression values.
- Open the track in table format by clicking on the table icon in the lower left side of the View Area.
- Genome Browser View Differentially Expressed Genes and Pathways () A collection of tracks presented together. Shows the human reference sequence, annotation tracks for genes, coding regions CDS, mRNA, and statistical comparison tracks (see figure 18.31).
- Heat Map for RNA-Seq () A two dimensional heat map of expression values. Each column corresponds to one sample, and each row corresponds to a feature (a gene or a transcript). The samples and features are both hierarchically clustered.
- Venn Diagram () To compare the overlap of differentially expressed genes or transcripts in two or more statistical comparison tracks.
- Expression Browser () To inspect gene and transcript expression level counts and statistics for many samples at the same time.
- GO Enrichment Analysis () A table showing the results of the GO enrichment analysis. The table includes GO terms, a description of the affected function/pathway, the number of genes in each function/pathway, the number of affected genes within the function/pathway, and p-values.
Please refer to the relevant sections of the the RNA-Seq Analysis tools chapter for additional information on the different output mentioned above.