Download the files gene_association.tair and gene_ontology.obo from and save them somewhere on your computer. This time, we will use a custom annotation and ontology file.
Which is basically a set of protein kinases. As an alternative to using the cluster you selected in the network, you can check the box Paste Genes from Text (shown below) and paste some white-space delimited gene names, e.g. Go to the BiNGO Settings panel (you DON'T have to start a new BiNGO session), choose a new cluster name and adjust some of the settings you made earlier. Go back to the network by clicking on the galFiltered.sif in the left panel on the Cytoscape desktop, and select another cluster of genes. Congratulations ! You just performed your first BiNGO analysis. The list of significantly overrepresented functional categories is shown in the BiNGO output window (more information on the cluster and options you selected, and on which genes did not produce any annotation, is stored in the test.bgo file). Regardless of the layout you choose, you'll probably have to tweak the nodes a little in order to avoid overlapping node labels. hierarchical, select the corresponding option from the Cytoscape Visualization menu. For more significant p-values, the node color gets increasingly more orange (see also the Color Legend panel). Yellow nodes represent GO categories that are overrepresented at the significance level. Uncolored nodes are not overrepresented, but they are the parents of overrepresented categories further down. Finally, a visualization of the overrepresented GO categories is created in Cytoscape. The program will inform you of its progress while parsing the annotations and calculating the tests, corrections and layout. Finally, select a directory to save the output file in (the file will be named test.bgo if you filled in test as a cluster name), and press Start BiNGO.
Cytoscape 3 tutorial code#
We want to consider all evidence codes, so don't fill in anything in the evidence code box. Select GO_Biological_Process from the ontology list, and Saccharomyces cerevisiae from the organism list. We're interested in assessing the overrepresentation of functional categories in our cluster with respect to the whole yeast genome, which is why we choose the Complete Annotation as the reference set. Since we only want to visualize those GO categories that are overrepresented after multiple testing correction, and their parents in the GO hierarchy, select the corresponding visualization option. 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. The corresponding boxes are checked accordingly by default. We want to assess overrepresentation of GO categories, and we want to visualize the results in Cytoscape. Check the box Get Cluster from Network (see below for an example with text input). 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 cluster.
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