QUEST

QUEST is a suite of tools implemented to support the deposition and analysis of data captured in genomic, in particular epigenetic, studies. The design of QUEST was originally motivated by the needs of researchers at the Center for Integrative Cancer Biology (CICB) at the Ohio State University and at Indiana University to navigate and analyze large databases of epigenetic data. QUEST has since evolved from being a pure ad-hoc query tool for interrogating databases into a platform for data management, query, and analysis. By presenting an intuitive and easy to use graphical user interface, QUEST enables users to build complex queries without a deep understanding of the underlying relational database structure, while alleviating the need to write tedious SQL statements or custom programs via a scripting language. As researchers acquire more data or data of differing types, they can add it to their "data stores" and QUEST will reflect the new entities in its GUI, allowing users to query the newly acquired data types. This can all be accomplished without a new programming endeavor.

The current implementation of QUEST consists of several components: a web-based graphical query interface (GUI), a web-based data uploading tool, a server backend that maintains the database system, and interfaces to external bioinformatics tools. A data model in QUEST defines not only the attributes of data elements, but also how they can be integrated through joins specified in the model. The data model is created and published by the database administrator to specify tables and relationships (joins) between them. The web-based query interface allows researchers to compose a query against the published data model using the GUI without having to write complex SQL queries. The web-based interface allows a user to save a query so other users can access it, tweak its parameters, and execute it without creating a query from scratch. As more data are added to the respective databases (e.g., promoter elements, sequence data, miRNA predictions, microarray data, validation data), new and saved queries from users can be rapidly executed. The tool allows the user to download the query results into a CSV or Excel file. Users can also query into multiple databases and send the results of their queries to other bioinformatics tools. Currently we have integration with GenePattern (http://www.broad.mit.edu/cancer/software/genepattern/) developed at the MIT Broad Institute and the UCSC Genome Browser (http://genome.ucsc.edu/). The data uploading tool assists the user with uploading their data to the system. It currently supports several file formats and carries out all the steps to populate and update the various tables in the database system.

In its current deployment at CICB, QUEST provides an for biologists to query, integrate, and examine their data across different types of experiments (e.g., Chromatin-immunoprecipitation microarray or ChIP-chip, global methylation profiling by Differential Methylation Hybridization or by 5-methyl-cytosine Immunoprecipitation, and gene expression profiling) and microarray platforms (e.g., Agilent 44-, 185-, and 244K oligonucleotide-based CpG island microarrays and Affymetrix human U133plus2 gene expression microarray). Data obtained from these experiments are deposited in the system whereby these data can be queried according to gene annotations, parameters associated with genetic and epigenetic data, etc. Some of the common queries (e.g., How many hypermethylated probes with ratio = 2 also have a gene expression probe ratio = 0.5?) are saved and can be re-executed with modified parameters to provide ease of use for the biologists. Once the researcher has queried the database, she/he can send the results to analytical modules.

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