Fisher's Exact Test

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Blast2GO has integrated the FatiGO package for statistical assessment of annotation differences between 2 sets of sequences. This package uses the Fisher's Exact Test and corrects for multiple testing. For this analysis, the completion (but not exclusively) of the involved sequences with their annotations must be loaded in the application. This can either be the result of a Blast2GO annotation or the imported annotation by file (.annot), see Gene Ontology Annotation Section of this manual.

This functionality can be found under Analysis → Enrichment Analysis (Fisher's Exact Test). A dialog screen appears (see image below). Test and Reference Sequences can be selected by uploading text files or ID-List .b2g files containing the lists of sequence IDs for the 2 groups. When there is no reference set selected, the whole dataset present in the project will be taken as reference. A detailed description of each parameter is available by clicking the help icon next to the parameter.

New: starting from Blast2GO 4.1 It is possible to perform the Fisher's Exact Test for different types of annotations for most of the results generated in Blast2GO. The Annotations parameter allows to select the column of the table to use as annotation. With this feature It is possible to perform an enrichment analysis of enzymes or InterPro IDs for example.

Fisher's Exact Test Wizard

Figure 1: Run Fisher's Exact Test Wizard Dialog

Click on the Run button to start the analysis. It may take a while depending on the number of annotations and your subscription (with a PRO subscription will be much faster).

Results Table

Once completed the results table will be shown in a new tab (see image below), where the adjusted p-values of each annotation above a given threshold will be shown. The main columns are:

Corrected p-value by False Discovery Rate control according to Benjamini-Hochberg.p-Value without multiple testing corrections

For further details please refer to the FatiGO publication (Al-Shahrour, F., Díaz-Uriarte, R., and Dopazo, J. (2004). Fatigo: a web tool for finding significant associations of gene ontology terms with groups of genes. Bioinformatics, 20(4):578–580).

Enrichment Result Table

Figure 2: Enrichment Results Table

Using the context menu of each row It is possible to get more details about the annotation and also create an ID-List with the sequences annotated in the Test-Set or the Reference-Set.

  • #Test is the number of sequences that are annotated with the GO and are in the test-set.
  • #NotAnnotTest is the number of sequences that are not annotated with that GO, that are in the test-set. 

Adding these two numbers it gives the total amount of sequences that are annotated at all in your test set e.g. GO:0061135: 9 + 52 = 61

Sidebar Options

In the sidebar there are located all possible action that can be performed for this enrichment result, including two options for the visual display of the results:

  1. Make Enriched Graph (only for GO annotations): use this option to generate a representation on the GO DAG (see image below). Nodes are color-highlighted proportionally to their significance value. The user can choose which type of calculated p-value to use for highlighting and the threshold for filtering out nodes. Additionally, the Filter intermediate checkbox will hide non-enriched nodes. More options are available in the graph viewer's sidebar. Gene Ontology Graphs Section of this manual gives further information on the graphical functions in Blast2GO.

Enrichment Graph

Figure 3: Enriched Graph

2. Show Bar Chart: this option generates a bar display of the percentages of sequences at both, test and reference set, for each annotation of the table (see image below).

Enrichment Bar Chart

Figure 4: Enriched Bar Chart

3. Reduce to Most Specific (only for GO annoations): use this option to remove more general GO terms from the results and get only the most specific terms (with the lowest level in the GO DAG).

Additionally, like many others results in Blast2GO, It is possible to display the enrichment results in two different ways: the Treemap representation to compare the most enriched annotations by their size and the WordCloud representation to summarise relevant annotations in a fashionable way.