BioMart--biological queries made easy

Abstract

Background: Biologists need to perform complex queries, often across a variety of databases. Typically, each data resource provides an advanced query interface, each of which must be learnt by the biologist before they can begin to query them. Frequently, more than one data source is required and for high-throughput analysis, cutting and pasting results between websites is certainly very time consuming. Therefore, many groups rely on local bioinformatics support to process queries by accessing the resource's programmatic interfaces if they exist. This is not an efficient solution in terms of cost and time. Instead, it would be better if the biologist only had to learn one generic interface. BioMart provides such a solution.

Results: BioMart enables scientists to perform advanced querying of biological data sources through a single web interface. The power of the system comes from integrated querying of data sources regardless of their geographical locations. Once these queries have been defined, they may be automated with its "scripting at the click of a button" functionality. BioMart's capabilities are extended by integration with several widely used software packages such as BioConductor, DAS, Galaxy, Cytoscape, Taverna. In this paper, we describe all aspects of BioMart from a user's perspective and demonstrate how it can be used to solve real biological use cases such as SNP selection for candidate gene screening or annotation of microarray results.

Conclusion: BioMart is an easy to use, generic and scalable system and therefore, has become an integral part of large data resources including Ensembl, UniProt, HapMap, Wormbase, Gramene, Dictybase, PRIDE, MSD and Reactome. BioMart is freely accessible to use at http://www.biomart.org.

Figure 1

BioMart query showing that the St18 gene is the only mouse gene in the first 10 Mb of chromosome 1 that is annotated as "targeting complete" by the International Mouse Mutagenesis Consortium. This involves: (A) selecting the Ensembl Mus musculus genes dataset, (B) setting the filters, (C) setting the attributes, (D) viewing the results, and (E) adding in the Gene targeting dataset to obtain just the gene that has reached the "targeting complete" status.

Figure 2

(A) Sequence output options and (B) FASTA output for all the genes found to be up-regulated in a microarray experiment using the Affymetrix HG-U95Av2 probeset. Here 1000 bp upstream of the first exon have been chosen along with the Ensembl Gene Id and the chromosomal position of the gene for the FASTA header.

Figure 3

Candidate gene identification using BioMart. (A) The Arrhythmogenic right ventricular dysplasia (ARVD) gene was mapped to 14q24. BioMart identifies 172 genes in this region, which may be narrowed down to 67 with expression in the heart. (B) This may be further refined to the two candidate genes, ZFP36L1 and TGFB3, by looking for genes involved in organ morphogenesis, according to GO, as this condition is known to result in widespread structural abnormalities. The latter gene is now known to be the one involved in this disorder. (C) BioMart may also be used to extract SNPs for the identified genes including their location in the gene, whether they are upstream, downstream, intronic or coding and for the latter whether they result in an amino acid substitution.