TOXICOGENOMICS ANALYSIS

The InforSense Toxicogenomics Solution provides an automated Quality Control (QC) and analysis platform to speed up the processing of gene expression data. It also supports the distribution of best practice analysis protocols to end user scientists. The solution draws on InforSense’s extensive experience building workflows and web portals to support gene expression data analysis. Experimental design data can be loaded to support comparison of design factors such as tissue and dose. Resulting gene lists can then be automatically validated in scientific literature using advanced text mining capabilities, or loaded into pathway tools to analyze their possible effects. The solution supports workflows and web pages out-of-the-box, but provides the flexibility and extensibility to be easily tailored to a customer’s environment.

With the vast amount of data being generated in gene expression experiments, there is commonly a backlog of data waiting to be QCed and analyzed. Bioinformatics teams are often overwhelmed by requests, with statisticians similarly under pressure. With the InforSense ToxicoGenomics Database solution, best practice analysis protocols can be set up by statisticians and made available to the wider community, ensuring consistent results. The solution enables these best practices to be deployed via a web portal to scientists, allowing them to perform their own QC and analysis. This saves considerable time and enables bioinformatics and statistician teams to more effectively support large groups of scientists. Scientists are also able to retrieve compound data from the corporate registration database and run sub-structure queries to find related compounds and display a SAR table for comparison.

As part of the solution QC workflows are provided to check that data is of sufficient quality for analysis and is integrated with Affymetrix Power Tools. Analysis workflows are also provided that support Tukey (Tukey-Kramer HSD), 1 and 2 way ANOVA and Principle Component Analysis (PCA) tools and are integrated with R to provide more advanced capabilities. A staged analysis uses the ANOVA tests to filter data at a high level before running more intensive PCA on the restricted data set

The solution also enables managers to see an overview of the current status of experiments improving the tracking and oversight of these projects. This view also enables comparisons to be made between groups with and without side effects for different doses and compounds. Ad-hoc experiments can also be designed in this interface by selecting and saving sets of animals to compare. The gene expression results can then be retrieved from a database and new QC and analysis workflows used to identify differential expression profiles that can then be used as possible biomarkers.

Annotation from typical bioinformatics resources can be used to help understand particular genes – information can be automatically retrieved from GenBank, UNI-PROT, ENSEMBL and GO using the solution. Genes can also be validated using integrated text mining capabilities that query PubMed for matches between gene lists, side effects of interest and appropriate linguistic relationships. In addition, the solution is integrated with pathway tools from GeneGo and Ingenuity allowing gene lists to be automatically sent to MetaCore and Ingenuity Pathway Assist and the resulting graphical views displayed.