GOSemSim: an R package for measuring semantic similarity among GO terms and gene products

@article{Yu2010GOSemSimAR,
  title={GOSemSim: an R package for measuring semantic similarity among GO terms and gene products},
  author={Guangchuang Yu and Fei Li and Yide Qin and Xiaochen Bo and Yibo Wu and Shengqi Wang},
  journal={Bioinformatics},
  year={2010},
  volume={26 7},
  pages={
          976-8
        }
}
SUMMARY The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. [] Key Method Four information content (IC)- and a graph-based methods are implemented in the GOSemSim package, multiple species including human, rat, mouse, fly and yeast are also supported. The functions provided by the GOSemSim offer flexibility for applications, and can be easily…
View on PubMed
academic.oup.com
746 Citations
Highly Influential Citations
57
Background Citations
48
Methods Citations
252
Results Citations
1

746 Citations

Citation Type

Citation Type

Gene Ontology Semantic Similarity Analysis Using GOSemSim.
TLDR
This chapter illustrates the use of GOSemSim on a list of regulators in preimplantation embryos with step-by-step analysis as well as instructions on interpretation and visualization of the results.
DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures
TLDR
The 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.
iNOA: An Improvement of Network Ontology Analysis with GO Semantic Similarity
TLDR
iNOA first retrieves the functions of all involved genes from the GO database, and then calculates the semantic similarity of the annotated terms in two genes as that in NOA, which indicates iNOA can obtain more effective and more specific GO functions than NOA and the other gene list methods.
ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity
The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional…
clusterProfiler: an R package for comparing biological themes among gene clusters.
TLDR
An R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters and can be easily extended to other species and ontologies is presented.
Identifying term relations cross different gene ontology categories
TLDR
An iterative ranking-based method called CroGO2 is proposed to measure the cross-categories GO term similarities by incorporating level information of GO terms with both direct and indirect interactions in the gene co-function network.
A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool
TLDR
A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis) is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures, allowing users to choose the most relevant semantic similarity approach for their biological applications.
Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes
TLDR
A method that incorporate enrichment of GO terms by a gene pair in computing their FS is proposed and it is shown that GO enrichment improves the performances of 46 existing FS measures in the prediction of sequence homologies, gene expression correlations, protein-protein interactions, and disease associated genes.
Investigating “Gene Ontology”- based semantic similarity in the context of functional genomics
TLDR
A novel algorithm, FuSiGroups, is developed, to group GO termsbased on their semantic similarity and genes based on their functional similarity, which results in groups of not only functionally similar genes but also an associated set of related GO terms that characterise a single functional aspect relating the genes in the group, which facilitates analysis by creating more coherent groups.
A Topology-Based Metric for Measuring Term Similarity in the Gene Ontology
TLDR
A new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG is introduced, thus enabling the measurement of functional similarities between proteins based on their GO annotations, and it is shown that it achieves good performance compared to the existing annotation-based GO measures.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 19 REFERENCES
GOSim – an R-package for computation of information theoretic GO similarities between terms and gene products
TLDR
The freely available software package GOSim is presented, which allows to calculate the functional similarity of genes based on various information theoretic similarity concepts for GO terms, and provides the researcher with a flexible and powerful tool to combine knowledge stored in GO with experimental data.
Evaluation of GO-based functional similarity measures using S. cerevisiae protein interaction and expression profile data
TLDR
This study evaluated five functional similarity methods using both protein-protein interaction (PPI) and expression data of S. cerevisiae and demonstrated the reliability of current approaches that elevate the similarities of GO terms to the similarity of proteins.
A new method to measure the semantic similarity of GO terms
TLDR
A novel method to encode a GO term's semantics into a numeric value by aggregating the semantic contributions of their ancestor terms in the GO graph is proposed and, in turn, an algorithm is designed to measure the semantic similarity of GO terms.
A new measure for functional similarity of gene products based on Gene Ontology
TLDR
A new method for comparing sets of GO terms and for assessing the functional similarity of gene products and a proposed map of the functional space provides a new global view on the functional relationships between gene products or protein families.
Gene Ontology term overlap as a measure of gene functional similarity
TLDR
The experiments suggest that term overlap can serve as a simple and fast alternative to other approaches which use explicit information content estimation or require complex pre-calculations, while also avoiding problems that some other measures may encounter.
Cluster analysis of protein array results via similarity of Gene Ontology annotation
TLDR
By determining the distances between annotations, the methodology reveals trends and enrichment of proteins of particular functions within high-throughput datasets at a higher sensitivity than perusal of end-point annotations.
Metrics for GO based protein semantic similarity: a systematic evaluation
TLDR
A systematic evaluation of GO-based semantic similarity measures using the relationship with sequence similarity as a means to quantify their performance, and assessed the influence of electronic annotations by testing the measures in the presence and absence of these annotations.
Investigating Semantic Similarity Measures Across the Gene Ontology: The Relationship Between Sequence and Annotation
TLDR
This paper investigates the use of ontological annotation to measure the similarities in knowledge content or 'semantic similarity' between entries in a data resource and shows a simple extension that enables a semantic search of the knowledge held within sequence databases.
Correlation between gene expression and GO semantic similarity
TLDR
This research analyzes some aspects of the relationship between gene expression, gene function, and gene annotation and deduces that there seems to be correlation between semantic similarity in the GO annotation and gene expression for the three GO ontologies.
Assessing protein similarity with Gene Ontology and its use in subnuclear localization prediction
TLDR
This work assesses protein similarity with Gene Ontology (GO) and then improves the performance of the system by adding a module of nearest neighbor classifier using a similarity measure derived from the GO annotation terms for protein sequences.
...
1
2
...