Functional Disease Ontology (FunDO)

Category Cross-Omics>Knowledge Bases/Databases/Tools

Abstract Functional Disease Ontology (FunDO) is a web-based application that explores genes using ‘Functional Disease Ontology’ annotations.

1) FunDO takes a list of genes and finds relevant diseases based on statistical analysis of the Disease Ontology (DO) annotation database.

Disease Ontology --

The Disease Ontology (DO) is a community driven, ‘open source’ ontology that is designed to link disparate datasets through ‘disease concepts’.

The manufacturers provide a computable structure of inheritable, environmental and infectious origins of human disease to facilitate the connection of genetic data, clinical data, and symptoms through the lens of human disease.

The manufacturers hope and anticipate that this will be useful for coupling disease concepts in model organisms to human disease concepts.

The Disease Ontology (DO) should enable the cross-walk between ‘disease concepts’, genes contributing to disease, and the ‘cloud’ of associated symptoms, findings and signs.

The use of the disease ontology (DO) requires these connections to be done, through evidence-based associations.

The understanding of disease and the association of disease with phenotype, environment, and genetics is dynamic and a reflection of current knowledge.

2) FunDO provides analysis of disease terms associated with genes in a gene list, similar to Gene Ontology analysis via DAVID.


The Database for Annotation, Visualization and Integrated Discovery (DAVID) 2008 is the sixth version of the original web-accessible software.

DAVID provides a comprehensive set of ‘Functional Annotation Tools’ for investigators to understand biological meaning behind a large list of genes (see G6G Abstract Number 20263).

3) Converting ‘gene identifiers’ to the proper format for input to FunDO --

FunDO accepts ‘Entrez gene IDs’ (for human genes) or gene symbols. Gene identifiers should be whitespace or comma separated.

Many statistical analysis packages for microarray data can directly output this format.

Note: If you have identifiers in another format, the manufacturers suggest using the ‘Gene ID Conversion Tool’ from DAVID.

4) Difference between GO analysis and DO analysis case study --

The manufacturer's used a gene list from a ‘pancreatic cancer’ study (Iacobuzio-Donahue et al., American Journal of Pathology 2003; 162: 1151-1162) to illustrate the difference between GO and DO analysis.

Briefly, a list of 125 genes identified in that study was used for further functional analysis.

The GO analysis was conducted using DAVID whereas the DO analysis was conducted using FunDO.

As expected, results from GO analysis suggest fundamental ‘biological processes’, such as protein binding, structural molecular activity, and structural constituents of cytoskeleton.

In contrast, results from FunDO analysis suggest disease associations, such as cancer metastasis, sarcoma, breast, lung, colon, and pancreatic caner.

In particular, the FunDO analysis suggests the significance of 23 genes associated with cancer metastasis, which was Not discussed in the original paper.

This new finding provides clues to potentially ‘new molecular markers’ for the surveillance and treatment of pancreatic cancer.

5) For a detailed description of how the Disease Ontology (DO) annotation database is generated from GeneRIFs (see below...); please see the paper - Annotating the human genome with Disease Ontology BMC Genomics 2009, 10(Suppl 1):S6doi:10.1186/1471-2164- 10-S1-S6.

GeneRIF -- Gene Reference Into Function --

GeneRIF provides a simple mechanism to allow scientists to add to the functional annotation of genes described in ‘Entrez Gene’.

(Entrez Gene is a searchable database of genes, from RefSeq genomes, and defined by sequence and/or located in the NCBI Map Viewer).

GeneRIFs are intended to facilitate access to publications documenting experiments that add to the understanding of a gene and its function.

6) A condensed version of the Disease Ontology (DO), 'Disease Ontology Lite', is actually used in FunDO.

FunDO Disease Ontology Lite (DOLite) --

In terms of contributions to ‘biological databases’, the manufacturers created DOLite, the first simplified version of the DO, and utilized DOLite to annotate the human genome.

In terms of methodological contribution, the manufacturers defined statistical methods to simplify a ‘general-purpose ontology’.

In contrast, the previous construction of Gene Ontology (GO) Slim from GO was largely a subjective process based on expert opinion.

The major contributions in methodology include computing the ontology similarity based on ‘gene-to-ontology mapping profiles’ (derived from GeneRIF -- see above…); defining two (2) types of ‘binary distance metrics’ to separately measure the overall similarities and subset similarities and a compactness-scalable ‘fuzzy clustering method’ (clustering results were verified with the constraints of semantic distance between DO terms).

This methodology can be easily adapted to slim other ontologies, like GO.

FunDO Documentation --

FunDO provides an interesting ‘Video Tutorial’ that takes you through all the steps of the analysis process.

System Requirements

Web-based - The manufacturers are using the ‘Google Visualization API’ to display the results table. If you canNot see this table, try using another browser. Firefox, Safari, and Chrome are all known to render the output table properly. Any other ‘standards compliant’ browser is also expected to work.


Manufacturer Web Site FunDO

Price Contact manufacturer.

G6G Abstract Number 20550

G6G Manufacturer Number 104164