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Help-page : POEAS - Plant Ontology Enrichment Analaysis Server:
POEAS - Help Index:
POEAS - Introduction:

Effective utilization of biomedical ontologies help in the interpretation of global trends associated with genes or proteins identified from high-throughput experiments. Analytical approaches like Gene Set Enrichment Analsis (GSEA) and Gene Ontology (GO) enrichment analysis provides global functional trends of gen es and proteins charecterized from a functional experiments. POEAS is a web server to utilize plant specific Plant Ontology (PO) for enrichment analysis. Phenomic analysis of gene lists can provide an important layer of information for performing new experiments to understand plant systems. Systematic interpretation of gene or proteins identified from high-throughput experiments using phenotype annotations help to understand the phenomic associations. Plant Ontology (PO) offers an ontological framework for describing plant phenomic charecterestics including plant anatomy, morphology and plant development stages. Adoption of this highly useful ontology was limited due to unavailability of tools to use the ontology for statistical enrichment analysis. To address this problem, we introduce POEAS: a plant ontology enrichment analysis server in the public domain. The server uses a simple list of genes as an input and perform enrichment analysis and provide results in two levels: a table with enrichment results and a visulaization utilitity to generate ontological graphs that can be used in publications. We envisage that Availability of such a tool as a complementary resource will enable both plant biologists and computational biologist to adopt plant ontology based phenomic analysis as part of analytical workflows.

Biological Enrichment Analysis using Ontologies and Annotations:

To perform biological enrichment analysis using ontologies the following data sets are required:

  • 1. List of genes perturbed in an experiment (say microarray, next-gen sequencing, proteomics etc)
  • 2. Background list of genes for your study (this could be list of genes that you have used to derive the perturbed genes from microarray, ngs, proteomics etc. For example, list of genes in a microarray, genes in a given genome etc.)
  • 3. A biomedical ontology (for example Gene Ontology or Plant Ontology)
  • 4. Association file (In this file you can find GO terms from assigned to genes in lists mentioned in 1 and 2)
NB: There are several well-defined biomedical ontologies available at NCBO BioPortal and OBO Foundry, but many of the ontologies dont have association files to perform enrichment analysis (other approaches similar to GSEA can be used in such situation using genes grouped as "sets" or "categories".

Biological enrichment analysis using biomedical ontologies and gene or protein-centric annotation data are classified into 3 categories by Huang et. al as singular enrichment analysis(SEA), gene set enrichment analysis (GSEA) and modular enrichment analysis (MEA). Basic difference between these three classes of enrichment algorithms are in the way the enrichment p-values are calculated.

In SEA-based approach, annotations terms of subset of genes are assessed one at a time against a list of background genes. An enrichment p-value is calculated by comparing the observed frequency of an annotation term with the frequency expected by chance and individual terms beyond the p-value cut-of (P-value ≤ 0.05). FunctAssociate and Onto-express are two SEA based enrichment analysis tools. GSEA approaches are similar, but consider all genes during the enrichment analysis, instead of a pre-defined threshold based genes as in the SEA approach. GSEA from broad is an example of GSEA based tool. MEA based programs like Ontologizer 2.0 and topGO use the relationship that exist between the annotations. These programs were reported to attain better sensitivity and specificity due to the consideration of GO term relationships. These tools are based on similar Statistical / algorithmic concepts. See a review on 68 tools published in 2008 (See Huang da W et.al). Statistical methods to derive P-value includes Fisher’s exact test, hypergeometric function, binomial test, χ2 test or combination of these methods. You can use one of the R package / servers / command-line tools for performing such analysis. While several Gene Ontology enrichment tools are available in the public no server implementation or command-line tool is available to perform Plant Ontology to perform enrichment analysis. POEAS is designed to fill this gap, to provide plant biologists and computational plant biologist an easy-to-use platform for enrichment analysis plant-specific, phenomics oriented Plant Ontology annotations.

Plant Ontology (PO):
Gene Ontology annotation extensively capture generic molecular information pertaining to genes and gene products, nevertheless it does not capture organism specific features like plant phenotypes or plant specific characteristics. To better illustrate plant specific properties in an ontology framework, Plant Ontology project is launched as a complementary resource to catalog phenotypic information on plants. Plant Ontology is a semantic framework that capture phenotype data sets from biological and genomic experiments. Initially it was designed as a two category ontology as “plant anatomical entity” and “plant structure development stage", as per current release: Plant Ontology recommends usage of a single ontology file for ontology based studies, but at the time of this writing (December 2012) the .obo and association files were provided by TAIR in two separate files as "temporal" and "anatomy". POEAS currently provides a web-platform for performing enrichment analysis of Plant Ontology terms using genes from Arabidopsis thaliana
Plant Ontology Enrichment Analysis: :
Table: 1 - Comparison of enrichment analysis using Gene Ontology (GO) and Plant Ontology (PO)
OntologyOntology Sub-setsOntology Association DataTools for Enrichment Analysis
Gene Ontology (GO)Biological Process, Cellular component and Molecular FunctionAvailable for various genomes at EBI-GOAVarious tools available; See list of tools at AmiGO here
Plant Ontology (PO)Plant Anatomical Entity (anatomy) and Plant Structure Development Stage (temporal)Available for limited number of plant genomesPlant Ontology Enrichment Analysis Server (POEAS)
POEAS - Methodology:

POEAS uses a simple list of The Arabidopsis Information Resource (TAIR) locus identifiers as input and perform enrichment analysis and provide results and tools for visualizing enrichment results. Enrichment analysis was performed using Ontologizer 2.0, a biomedical ontology enrichment analysis tool, multiple options are availble to select enrichment method and statistical approaches for multiple testing correction. If we start off with a list of 700 Arabidopsis thaliana genes responsive to abscisic acid stress obtained from Stress Responsive Transcription Factor Database, version 2 (STIFDB2), a user can input 700 TAIR locus identifiers as input and select multiple-testing correction method, enrichment calculation method and resampling steps to perform the enrichment analysis. We performed Plant Ontology enrichment analysis using following parameters using POEAS:

  • Select multiple-testing correction method: Bonferroni
  • Enrichment calculation method: Term-For-Term
  • Resampling steps: 1000
The output from this analysis provided extensive information on plant phenotypic characteristics.The genes were also influence plant phenotype in multiple levels of plant structure development stage (temporal) and plant anatomy. A total of 65 enriched plant anatomy terms and 20 temporal terms were significantly enriched. The most significant terms includes genes associated with "cotyledon", "pollen", "microgametophyte", "pollen sac" etc. Users can also visualize genes in a diacyclic graph layout using Graphviz based dot tool. The web interface of POEAS is developed using HTML, CSS and JavaScript. PO annotations and association data are synced to POEAS to provide uptodate results to the users.

POEAS - Input details:
POEAS - Output details:
  • Significant Plant Ontology Terms
  • Visualize Plant Ontology Terms
  • Plant Ontology - Gene Annotation
  • Download

POEAS - References:

  • The Plant Ontology Consortium (2002) The Plant Ontology Consortium and plant ontologies. Comp Funct Genomics, 3, 137-142.
  • Bauer, S., Grossmann, S., Vingron, M. and Robinson, P.N. (2008) Ontologizer 2.0--a multifunctional tool for GO term enrichment analysis and data exploration. Bioinformatics, 24, 1650-1651.
  • Avraham, S., Tung, C.W., Ilic, K., Jaiswal, P., Kellogg, E.A., McCouch, S., Pujar, A., Reiser, L., Rhee, S.Y., Sachs, M.M. et al. (2008) The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations. Nucleic Acids Res, 36, D449-454.
  • Cooper, L., Walls, R.L., Elser, J., Gandolfo, M.A., Stevenson, D.W., Smith, B., Preece, J., Athreya, B., Mungall, C.J., Rensing, S. et al. (2012) The Plant Ontology As A Tool For Comparative Plant Anatomy And Genomic Analyses. Plant & cell physiology.
  • Jaiswal, P., Avraham, S., Ilic, K., Kellogg, E.A., McCouch, S., Pujar, A., Reiser, L., Rhee, S.Y., Sachs, M.M., Schaeffer, M. et al. (2005) Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages. Comp Funct Genomics, 6, 388-397.
  • Huang da W, Sherman BT, Lempicki RA. (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists Nucleic Acids Res. 2009 Jan;37(1):1-13.
  • Tipney H, Hunter L. (2010) An introduction to effective use of enrichment analysis software. Hum Genomics. 2010 Feb;4(3):202-6.
  • Rhee SY, Wood V, Dolinski K, Draghici S. (2008) Use and misuse of the gene ontology annotations. Nat Rev Genet. 2008 Jul;9(7):509-15.
POEAS - Team :
Prof. Ramanthan Sowdhamini (Contact : mini@ncbs.res.in)
Khader Shameer
Oommen K. Mathew
Mahantesha Naika