GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis

By Qi Zheng, Xiu-Jie Wang. Nucleic Acids Res., 2008

652 citations recorded by the source corpus.

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data. Although there have been a lot of software with GO-related analysis functions, new tools are still needed to meet the requirements for data generated by newly developed technologies or for advanced analysis purpose. Here, we present a Gene Ontology Enrichment Analysis Software Toolkit (GOEAST), an easy-to-use web-based toolkit that identifies statistically overrepresented GO terms within given gene sets. Compared with available GO analysis tools, GOEAST has the following improved features: (i) GOEAST displays enriched GO terms in graphical format according to their relationships in the hierarchical tree of each GO category (biological process, molecular function and cellular component), therefore, provides better understanding of the correlations among enriched GO terms; (ii) GOEAST supports analysis for data from various sources (probe or probe set IDs of Affymetrix, Illumina, Agilent or customized microarrays, as well as different gene identifiers) and multiple species (about 60 prokaryote and eukaryote species); (iii) One unique feature of GOEAST is to allow cross comparison of the GO enrichment status of multiple experiments to identify functional correlations among them. GOEAST also provides rigorous statistical tests to enhance the reliability of analysis results. GOEAST is freely accessible at http://omicslab.genetics.ac.cn/GOEAST/

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/314394396fe89512af1347294945672c410e6b04

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Citations in the corpus

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists (2008, neutral): “Tools, such as GOBar (32), Go-Mapper (22), GOAlie, PageMan (51), high-throughput GoMiner (39), and the most recent, GOEAST (70), are intended to provide some of these capabilities to display multiple time course datasets simultaneously.”
Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges (2012, neutral): “cn/GOEAST/) [75]”
ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems (2010, methodology): “Progress in this area is shown in recent tools such as High-Throughput GoMiner (9) and GOEAST (10); however, these tools currently enable only Gene Ontology-based set enrichments and would be insensitive to regulatory mechanisms, protein–protein interactions, phenotypes, diseases, small molecule…”
Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods (2013, methodology): “These methods are popular among GO-based tools (6), including BiNGO (7), DAVID (8), GOstat (9) and GOEAST (10).”
Transcriptomic responses to heat stress and bleaching in the elkhorn coral Acropora palmata (2010, methodology): “J Biol Chem 278:36953–36958 Zheng Q, Wang XJ (2008) GOEAST: a web-based software toolkit for gene ontology enrichment analysis.”
Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease (2011, neutral): “rs1378938 15 72,397,784–73,270,664 (23; 873) 0.”
The molecular mechanism of action of bactericidal gold nanoparticles on Escherichia coli. (2012, methodology): “We obtained biological processes related to down-regulated and up-regulated genes by GO enrichment analysis [34] (Tables 1 and 2) and the concerned biological pathway related to the differently expressed genes with minimal p value by analysis of KEGG pathway database (Table 3).”
MSEA: a web-based tool to identify biologically meaningful patterns in quantitative metabolomic data (2010, background): “Its success has also inspired many extensions, improvements and variations (8–16).”
Mining breast cancer genes with a network based noise-tolerant approach (2013, methodology): “DAVID and GOEAST are online tools and GOstats is an R package from Bioconductor [56].”