Abstract
Gene ontology (GO) is a controlled vocabulary of gene functions across all species, which is widely used for functional analyses of individual genes and large-scale proteomic studies. NaviGO is a webserver for visualizing and quantifying the relationship and similarity of GO annotations. Here, we walk through functionality of the NaviGO webserver (http://kiharalab.org/web/navigo/) using an example input and explain what can be learned from analysis results. NaviGO has four main functions, accessed from each page of the webserver: “GO Parents,” “GO Set”, “GO Enrichment”, and “Protein Set.” For a given list of GO terms, the “GO Parents” tab visualizes the hierarchical relationship of GO terms, and the “GO Set” tab calculates six functional similarity and association scores and presents results in a network and a multidimensional scaling plot. For a set of proteins and their associated GO terms, the “GO Enrichment” tab calculates protein GO functional enrichment, while the “Protein Set” tab calculates functional association between proteins. The NaviGO source code can be also downloaded and used locally or integrated into other software pipelines.
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References
Consortium GO (2013) Gene ontology annotations and resources. Nucleic Acids Res 41(D1):D530–D535
Ashburner M, Ball C, Blake J, Botstein D, Butler H, Cherry J, Davis A, Dolinski K, Dwight S, Eppig J (2000) Gene ontology: tool for the unification of biology. The gene ontology consortium. Nat Genet 25(1):25–29. https://doi.org/10.1038/75556
Wei Q, Khan IK, Ding Z, Yerneni S, Kihara D (2017) NaviGO: interactive tool for visualization and functional similarity and coherence analysis with gene ontology. BMC Bioinformatics 18(1):177. https://doi.org/10.1186/s12859-017-1600-5
Carbon S, Ireland A, Mungall CJ, Shu S, Marshall B, Lewis S (2009) AmiGO: online access to ontology and annotation data. Bioinformatics 25(2):288–289. https://doi.org/10.1093/bioinformatics/btn615
Binns D, Dimmer E, Huntley R, Barrell D, O'donovan C, Apweiler R (2009) QuickGO: a web-based tool for gene ontology searching. Bioinformatics 25(22):3045–3046
Hawkins T, Luban S, Kihara D (2006) Enhanced automated function prediction using distantly related sequences and contextual association by PFP. Protein Sci 15(6):1550–1556. https://doi.org/10.1110/ps.062153506
Hawkins T, Chitale M, Luban S, Kihara D (2009) PFP: automated prediction of gene ontology functional annotations with confidence scores using protein sequence data. Proteins 74(3):566–582. https://doi.org/10.1002/prot.22172
Chitale M, Hawkins T, Park C, Kihara D (2009) ESG: extended similarity group method for automated protein function prediction. Bioinformatics 25(14):1739–1745. https://doi.org/10.1093/bioinformatics/btp309
Khan IK, Qing W, Kihara D (2015) PFP/ESG: automated protein function prediction servers enhanced with gene ontology visualization tool. Bioinformatics 31(2):271–272. https://doi.org/10.1093/bioinformatics/btu646
Pundir S, Martin MJ, O'Donovan C (2017) UniProt protein knowledgebase. Methods Mol Biol 1558:41–55. https://doi.org/10.1007/978-1-4939-6783-4_2
Dieterle M, Bauer D, Büche C, Krenz M, Schäfer E, Kretsch T (2005) A new type of mutation in phytochrome A causes enhanced light sensitivity and alters the degradation and subcellular partitioning of the photoreceptor. Plant J 41(1):146–161
Nito K, Wong CC, Yates JR, Chory J (2013) Tyrosine phosphorylation regulates the activity of phytochrome photoreceptors. Cell Rep 3(6):1970–1979
Al-Sady B, Ni W, Kircher S, Schäfer E, Quail PH (2006) Photoactivated phytochrome induces rapid PIF3 phosphorylation prior to proteasome-mediated degradation. Mol Cell 23(3):439–446
Liu X, Chen C-Y, Wang K-C, Luo M, Tai R, Yuan L, Zhao M, Yang S, Tian G, Cui Y (2013) PHYTOCHROME INTERACTING FACTOR3 associates with the histone deacetylase HDA15 in repression of chlorophyll biosynthesis and photosynthesis in etiolated Arabidopsis seedlings. Plant Cell 25(4):1258–1273
Ito S, Nakamichi N, Nakamura Y, Niwa Y, Kato T, Murakami M, Kita M, Mizoguchi T, Niinuma K, Yamashino T (2007) Genetic linkages between circadian clock-associated components and phytochrome-dependent red light signal transduction in Arabidopsis thaliana. Plant Cell Physiol 48(7):971–983
Resnik P (1995) Using information content to evaluate semantic similarity in a taxonomy. arXiv preprint cmp-lg/9511007
Lin D (1998) An information-theoretic definition of similarity. In: ICML, vol 1998. Citeseer, pp 296–304
Schlicker A, Domingues F, Rahnenführer J, Lengauer T (2006) A new measure for functional similarity of gene products based on gene ontology. BMC Bioinformatics 7:302. https://doi.org/10.1186/1471-2105-7-302
Yerneni S, Khan I, Wei Q, Kihara D (2015) IAS: interaction specific GO term associations for predicting protein-protein interaction networks. IEEE/ACM Trans Comput Biol Bioinform. https://doi.org/10.1109/TCBB.2015.2476809
Chitale M, Palakodety S, Kihara D (2011) Quantification of protein group coherence and pathway assignment using functional association. BMC Bioinformatics 12(1):373
Hawkins T, Chitale M, Kihara D (2010) Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP. Bmc Bioinformatics 11(1):265
Clack T, Shokry A, Moffet M, Liu P, Faul M, Sharrock RA (2009) Obligate heterodimerization of Arabidopsis phytochromes C and E and interaction with the PIF3 basic helix-loop-helix transcription factor. Plant Cell 21(3):786–799
Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, Santos A, Doncheva NT, Roth A, Bork P, Jensen LJ, von Mering C (2017) The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res 45(D1):D362–D368. https://doi.org/10.1093/nar/gkw937
Acknowledgments
We thank Charles Christoffer for proofreading the manuscript. This work was partly supported by the National Institute of General Medical Sciences of the NIH (R01GM123055) and the National Science Foundation (DBI1262189, IOS1127027, DMS1614777).
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Ding, Z., Wei, Q., Kihara, D. (2018). Computing and Visualizing Gene Function Similarity and Coherence with NaviGO. In: Mamitsuka, H. (eds) Data Mining for Systems Biology. Methods in Molecular Biology, vol 1807. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8561-6_9
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