SmartChip Pathway Analysis Panels

Determining disease signatures, especially for complex diseases, is evolving into the study of complete biological pathways. By investigating changes in gene expression with a single or several pathways, even subtle changes can be detected. With approximately 500 pathways available as pre-defined assay sets comprising ~9,000 assays WaferGen enables researchers to resolve biological complexity in a flexible, cost-effective manner. Now, with the SmartChip Pathway Analysis Panels, researchers can:

• Profile defined biological pathways for rapid results
• Screen a single pathway over hundreds of samples or combine multiple pathways on a single panel to adapt to a variety of experimental designs
• Specify lists of pathways, place the order, and WaferGen delivers the content on a SmartChip panel within 2-3 weeks

WaferGen SmartChip technology is the superior choice for pathway-based profiling and screening projects. Unlike global, discovery approaches employing techniques such as microarray screening and next-generation sequencing, which can lack sensitivity and can be costly, the SmartChip platform allows researchers to obtain highly accurate qPCR data with the flexibility to profile, validate or screen, all at a reasonable cost.

Next-Generation qPCR: The New Standard for Pathway Analysis

After the initial discovery phase, confirmation is best achieved through biological replicates (Fang and Cui, 2011). The discovery technologies are often cost-prohibitive, time-consuming, and not scalable. Enormous amounts of data are generated for every sample leading to a bioinformatics bottleneck. In contrast, SmartChip Panels may be configured to be broad–allowing for up to 1000′s of assays over a single sample per panel– or highly focused–e.g. running a dozen assays over several hundred samples. Confirmation of a pathway-based experiment using biological replicates with the SmartChip panel is a highly attractive solution.

Biological Pathway Analysis

The use of biological pathways for gene expression analysis is a routine approach for correlation of phenotypic changes or disease states (Emmert-Streib and Glazko, 2011). Pathways are chosen because subtle changes in expression levels of individual genes are often undetectable, whereas pathway analysis can detect disease-associated expression changes, for example in the case of Type II diabetes (Mootha et al., 2003). One of the first algorithms for pathway analysis, the Gene Set Enrichment Analysis (GSEA) algorithm, has gained increased acceptance and has currently been cited thousands of times as seen in the figure below (Subramanian et al., 2005). Similarly, a recent review has suggested that networks are the key link for common human diseases (Schadt, 2009).

Other examples where pathway analysis has been employed to solve complex problems are B-cell lymphoma (Alizadeh et al., 2000), cervical cancer (Martin et al., 2009) and kidney transplantation (Brouard et al., 2011).

Other well-recognized and established resources for pathway analysis are listed in the references below. To date, WaferGen has developed content for over 500 pathways–with > 85% gene coverage–totalling approximately 9,000 assays, and we are pleased to offer this tool to researchers for use in conjunction with the SmartChip Real-Time PCR system.

To investigate the specific pathways further, click here.

For more information or to request a quote, click here.