Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The . gov means it’s official. Federal government websites often end in VSports app下载. gov or . mil. Before sharing sensitive information, make sure you’re on a federal government site. .

Https

The site is secure V体育官网. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. .

. 2008 Jul 1;36(Web Server issue):W358-63.
doi: 10.1093/nar/gkn276. Epub 2008 May 16.

"V体育安卓版" GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis

Qi Zheng  1 , Xiu-Jie Wang
Affiliations

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

Qi Zheng et al. Nucleic Acids Res. .

Abstract

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data VSports手机版. 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/ .

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
The GOEAST graphical output of enriched GO terms in the biological process category for a sample experiment. Boxes represent GO terms, labeled by its GO ID, term definition, and detailed information, organized as ‘q/m|t/k (P-value)’ (see Materials and Methods section for the meanings of q, m, t and k). Significantly enriched GO terms are marked yellow. The degree of color saturation of each node is positively correlated with the enrichment significance of the corresponding GO term. Nonsignificant GO terms within the hierarchical tree are shown as white boxes. Branches of the GO hierarchical tree without significantly enriched GO terms are not shown. Arrows represent connections between different GO terms. Red arrows represent relationships between two enriched GO terms, black solid arrows represent relationships between enriched and unenriched terms and black dashed arrows represent relationships between two unenriched GO terms.
Figure 2.
Figure 2.
Graphical output of Multi-GOEAST analysis results for differentially expressed genes in Jmjd1a and Jmjd2c knockdown mice. Red and green boxes represent enriched GO terms only found in Jmjd1a knockdown mice (first experiment) or Jmjd2c knockdown mice (second experiment), respectively. Yellow boxes represent commonly enriched GO terms in both experiments. The saturation degrees of all colors represent the significance of enrichment for corresponding GO terms.
See this image and copyright information in PMC

References (V体育2025版)

    1. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene Ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 2000;25:25–29. - PMC - PubMed
    1. Khatri P, Draghici S, Ostermeier GC, Krawetz SA. Profiling gene expression using onto-express. Genomics. 2002;79:266–270. - PubMed
    1. Robinson MD, Grigull J, Mohammad N, Hughes TR. FunSpec: a web-based cluster interpreter for yeast. BMC Bioinform. 2002;3:35. - PMC (VSports最新版本) - PubMed
    1. Berriz GF, King OD, Bryant B, Sander C, Roth FP. Characterizing gene sets with FuncAssociate. Bioinformatics. 2003;19:2502–2504. - PubMed
    1. Castillo-Davis CI, Hartl DL. GeneMerge—post-genomic analysis, data mining, and hypothesis testing. Bioinformatics. 2003;19:891–892. - PubMed

Publication types