The immediate need for functional analysis of microarray gene expression data and the emergence of GO during that period gave rise to over-representation analysis (ORA), which statistically evaluates the fraction of genes in a particular pathway found among the set of genes showing changes in expression. It is also referred to as “2×2 table method” in the literature.
Analyzes interrelations of term and functional groups in biological networks. ClueGO offers the possibility to visualize terms corresponding to a list of genes and allows the comparison of functional annotations of two clusters. This Cytoscape plug-in contains Gene Ontology (GO) terms and KEGG/BioCarta pathways. This software can be also applied to new organisms, identifier types and annotation sources.
Permits functional annotation, management, and data mining of novel sequence data. Blast2GO is based on the utilization of common controlled vocabulary schemas, the gene ontology (GO). It takes in consideration similarity, the extension of the homology, the database of choice, the GO hierarchy, and the quality of the original annotations. This tool is suitable for plant genomics research. It generates functional annotation and assesses the functional meaning of their experimental results.
Allows users to perform gene ontology (GO) analysis on RNA-seq data. GOseq is a software that includes functions for calculating the significance of over-representation of each GO category amongst differentially expressed (DE) genes. These functions give researchers the possibility to select which type of bias they wish to compensate for, between two options: transcript length bias or total read count bias.
Serves for visualizing, comparing and plotting gene ontology (GO) annotation results. WEGO allows researchers to work with the directed acyclic graph structure of GO to simplify histogram creation of GO annotation results. Moreover, this program can be used for understanding GO annotations and supports the comparison between several gene datasets.
Allows users to obtain biological features/meaning associated with large gene or protein lists. DAVID can determine gene-gene similarity, based on the assumption that genes sharing global functional annotation profiles are functionally related to each other. It groups related genes or terms into functional groups employing the similarity distances measure. This tool takes into account the redundant and network nature of biological annotation contents.
Serves for the functional analysis of gene expression and genomic data. Babelomics offers the possibility to explore the effects of alteration in gene expression levels or changes in genes sequences within a functional context. It provides user-friendly access to a full range of methods that cover: (1) primary data analysis; (2) a variety of tests for different experimental designs; and (3) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context.
Identifies the statistical overrepresentation of Gene Ontology (GO) categories in a subgraph of a biological network or any other set of genes. BiNGO exploits Cytoscape’s visualization environment to represents molecular interaction networks. This software features annotations for a large range or organisms and even if designed primarily for GO ontology, can be utilized with other classification systems.