GOSim – an R-package for computation of information theoretic GO similarities between terms and gene products

Fröhlich, Holger; Speer, N.; Poustka, Annemarie; Beißbarth, Tim

doi:10.1186/1471-2105-8-166

Cited by 182 publications

(163 citation statements)

References 10 publications

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“…GOSim (Fröhlich et al, 2007), which allows calculating the semantic similarity between GO terms, was used to investigate whether the genes identified by previous steps are related to growth, immunity or both. First, we obtained the exact concepts 'growth' and 'development' that correspond to 'growth' and many immune processes corresponding to 'immunity' using MeSH database (Lowe and Barnett, 1994).…”

Section: Methodsmentioning

confidence: 99%

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Zhang

Wang

Yang

et al. 2016

animal

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Both growth and immune capacity are important traits in animal breeding. The animal quantitative trait loci (QTL) database is a valuable resource and can be used for interpreting the genetic mechanisms that underlie growth and immune traits. However, QTL intervals often involve too many candidate genes to find the true causal genes. Therefore, the aim of this study was to provide an effective annotation pipeline that can make full use of the information of Gene Ontology terms annotation, linkage gene blocks and pathways to further identify pleiotropic genes and gene sets in the overlapping intervals of growth-related and immunity-related QTLs. In total, 55 non-redundant QTL overlapping intervals were identified, 1893 growth-related genes and 713 immunity-related genes were further classified into overlapping intervals and 405 pleiotropic genes shared by the two gene sets were determined. In addition, 19 pleiotropic gene linkage blocks and 67 pathways related to immunity and growth traits were discovered. A total of 343 growth-related genes and 144 immunity-related genes involved in pleiotropic pathways were also identified, respectively. We also sequenced and genotyped 284 individuals from Chinese Meishan pigs and European pigs and mapped the single nucleotide polymorphisms (SNPs) to the pleiotropic genes and gene sets that we identified. A total of 971 high-confidence SNPs were mapped to the pleiotropic genes and gene sets that we identified, and among them 743 SNPs were statistically significant in allele frequency between Meishan and European pigs. This study explores the relationship between growth and immunity traits from the view of QTL overlapping intervals and can be generalized to explore the relationships between other traits.

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Section: Methodsmentioning

confidence: 99%

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Zhang

Wang

Yang

et al. 2016

animal

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“…The gene pairwise method defines a summary for the gene set score that is the best-match average of the separate gene pair similarity scores. Gene pair similarity scores were implemented by GOSim [36]. The gene set annotation method is based on the bestmatch average of the similarity scores between two annotated category sets for each score, which was implemented by GOSemSim in this study [37].…”

Section: Comparison With Other Methods Using Complex Functional Catalmentioning

confidence: 99%

A novel method to quantify gene set functional association based on gene ontology

Wang

et al. 2011

J. R. Soc. Interface.

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Numerous gene sets have been used as molecular signatures for exploring the genetic basis of complex disorders. These gene sets are distinct but related to each other in many cases; therefore, efforts have been made to compare gene sets for studies such as those evaluating the reproducibility of different experiments. Comparison in terms of biological function has been demonstrated to be helpful to biologists. We improved the measurement of semantic similarity to quantify the functional association between gene sets in the context of gene ontology and developed a web toolkit named Gene Set Functional Similarity (GSFS; http://bioinfo.hrbmu.edu.cn/GSFS). Validation based on protein complexes for which the functional associations are known demonstrated that the GSFS scores tend to be correlated with sequence similarity scores and that complexes with high GSFS scores tend to be involved in the same functional catalogue. Compared with the pairwise method and the annotation method, the GSFS shows better discrimination and more accurately reflects the known functional catalogues shared between complexes. Case studies comparing differentially expressed genes of prostate tumour samples from different microarray platforms and identifying coronary heart disease susceptibility pathways revealed that the method could contribute to future studies exploring the molecular basis of complex disorders.

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“…In the first step, the SP algorithm calculates the IC values for the terms on the graph using equation (2). In practice, several R packages (e.g., (Froehlich et al, 2007)) provide IC information for GO terms. Therefore, the IC values can be retrieved from these packages when needed.…”

Section: Ic T Ic T T Tmentioning

confidence: 99%

“…We used the GOSim package (Froehlich et al, 2007) to calculate the semantic similarity for Resnik's, Jiang's and the Relevance methods, and the GOSemSim package (Yu et al, 2010) for Wang's method.…”

Section: Data Description and Experimental Setupmentioning

confidence: 99%

Characterisation of semantic similarity on gene ontology based on a shortest path approach

Shen

Zhang

Wong

et al. 2014

IJDMB

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Semantic similarity defined on Gene Ontology (GO) aims to provide the functional relationship between different GO terms. In this paper, a novel method, namely the Shortest Path (SP) algorithm, for measuring the semantic similarity on GO terms is proposed based on both GO structure information and the term's property. The proposed algorithm searches for the shortest path that connects two terms and uses the sum of weights on the path to estimate the semantic similarity between GO terms. A method for evaluating the nonlinear correlation between two variables is also introduced for validation. Extensive experiments conducted on the PPI dataset and two public gene expression datasets demonstrate the overall superiority of SP method over the other stateof-the-art methods evaluated.

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GOSim – an R-package for computation of information theoretic GO similarities between terms and gene products

Cited by 182 publications

References 10 publications

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

A novel method to quantify gene set functional association based on gene ontology

Characterisation of semantic similarity on gene ontology based on a shortest path approach

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