Binomial Approximation to the Generalized Hypergeometric Distribution

Teerapabolarn, K.

doi:10.12732/ijpam.v83i4.4

Cited by 2 publications

(1 citation statement)

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“…Note that we are dealing with very large population size (organism’s genome, proteome or set of annotated proteins in the GOA file), in which case the size of the target gene or protein subset is very small compared to the population size. Thus, the p-value can also be approximated by or modeled using the binomial distribution [ 42 ] by taking the relative frequency of occurrence of each GO term in the reference dataset as an estimator of the probability p of observing the GO term under consideration. In this case, a gene taken at random from the reference dataset is an event with two possible outcomes, namely success (1), if the gene is annotated with the GO term, and failure (0) otherwise.…”

Section: Methodsmentioning

confidence: 99%

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures

Mazandu

Mulder

2013

BMC Bioinformatics

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BackgroundThe use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications.ResultsWe have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries.ConclusionsThe DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

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Section: Methodsmentioning

confidence: 99%