CYTOSCAPE TUTORIAL CODE

CYTOSCAPE TUTORIAL CODE

We want to consider all GO annotation evidence codes, so don't fill in anything in the evidence code box. Note that it is recommended in most cases to use custom annotation and ontology files instead, see further. We’ve already selected GO_Full from the ontology list, and now we select Saccharomyces cerevisiae from the organism list. We're interested in assessing the enrichment of functional categories in a gene’s neighborhood with respect to the whole yeast genome, which is why we choose the Whole Annotation as the reference set. Then select a statistical test (the Hypergeometric Test is exact and equivalent to an exact Fisher test, the Binomial Test is less accurate but quicker) and a multiple testing correction (we recommend Benjamini & Hochberg's FDR correction, the Bonferroni correction will be too conservative in most cases), and choose a significance level, e.g. Select Current Cytoscape network from the Choose network to analyze dropdown menu. If Star network is unchecked, connections between the neighbors will also be displayed. When Star network is checked, the output networks will only contain edges from candidate genes to neighbors of those genes in the input network (see below) that are annotated to one of the Target GO categories. The third checkbox next to the Multiple tabs checkbox controls the topology of the output network. In our case, it doesn’t matter whether the box is checked or not since we only specified one Target GO category. This is controlled by the Multiple tabs checkbox. The user also has the option of visualizing the results for different Target categories in separate output tabs and output networks. We want to visualize the results in Cytoscape, so the corresponding box is checked accordingly.

This is the predicted GO annotation we want the candidate genes to have. Finally, fill in 19953 in the Target GO categories field as well ( sexual reproduction = GO:0019953). Genes already annotated to this category will be filtered out, because we are not interested in discovering known reproduction genes. The text in the the Filter GO categories field should now read ‘19953‘ ( sexual reproduction = GO:0019953).

Search for ‘sexual+reproduction’, select the sexual reproduction GO category and transfer it to the Filter GO categories field by clicking the Add button. Close the search dialog and click the Search IDs button next to Filter GO categories. The GO ID code for the ‘ transcription factor activity’ category is transferred to the Start GO categories field. Select ‘ transcription factor activity’ from the list using the checkbox at the left, and click the Add button. Click the Search IDs button next to Start GO categories, and fill in ‘transcription+factor+activity’ in the search dialog (the +’s ensure that the search results will contain all three words, not just 1 or 2). Those categories are the classes of genes we want to explore, and in our case transcription factors. First of all, we will specify which Start GO categories we want to use. This choice determines which ontology terms can be used in the GO categories fields. Select GO_Full from the ontology list under Select ontology file. We want to discover transcription factors in the network that might be involved in the process of reproduction in yeast, but that are not yet annotated as such in GO. This name will be used for creating the output file and the visualization of the results in Cytoscape. Start by filling in a name for your analysis, e.g.

Cytoscape tutorial