AbstractBackgroundMicroarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services.ResultsWe developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems.ConclusionsWe provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.

It has been proposed that ZNF217, which is amplified at 20q13 in various tumors, plays a key role during neoplastic transformation. ZNF217 has been purified in complexes that contain repressor proteins such as CtBP2, suggesting that it acts as a transcriptional repressor. However, the function of ZNF217 has not been well characterized due to a lack of known target genes. Using a global chromatin immunoprecipitation (ChIP)-chip approach, we identified thousands of ZNF217 binding sites in three tumor cell lines (MCF7, SW480, and Ntera2). Further analysis of ZNF217 in Ntera2 cells showed that many promoters are bound by ZNF217 and CtBP2 and that a subset of these promoters are activated upon removal of ZNF217. Thus, our in vivo studies corroborate the in vitro biochemical analyses of ZNF217-containing complexes and support the hypothesis that ZNF217 functions as a transcriptional repressor. Gene ontology analysis showed that ZNF217 targets in Ntera2 cells are involved in organ development, suggesting that one function of ZNF217 may be to repress differentiation. Accordingly we show that differentiation of Ntera2 cells with retinoic acid led to down-regulation of ZNF217. Our identification of thousands of ZNF217 target genes will enable further studies of the consequences of aberrant expression of ZNF217 during neoplastic transformation.