Fast and flexible bioinformatics analysis of RNA seq data to provide biological insight

Jesper Culmsee Tholstrup
EXIQON, Denmark

In recent years, Next Generation Sequencing (NGS) has evolved from a novel technology to become an established method for investigating biological systems at the genetic level. Furthermore, ongoing advances in the underlying chemistry and associated instrumentation have led to the development of a number of semi-automated platforms that can be applied to a range of biological problems. In this way biological samples may be sequenced in a semi-automated and relatively trouble free manner.
However, analysis of the generated data remains a major obstacle; even a small sequencing run can generate vast quantities of data. While there are many commercial and open source software solutions available for analyzing NGS data, running these tools effectively in an automated manner remains a formidable challenge. Also, while an automated analysis can provide a general overview of the data (for example, mapping differentially expressed features, and Gene Ontology and Pathway enrichment) it does not generally provide deeper insight into the system under investigation. Furthermore, even for this basic analysis, the quantity of data generated can be overwhelming. Thus, more in-depth investigation and interpretation of raw sequence data remains an elusive task for many researchers who lack access to bioinformatics expertise and computing resources.
We have developed a flexible “plug and play” bioinformatics platform that allows customizable NGS analyses which can be tailored to specific needs on a case by case basis for RNA sequencing. The platform has the flexibility to incorporate existing steps or permit the creation of new steps which perform novel analyses in terms of method, reference data, or data visualization. In this way, a NGS dataset can be mined in greater depth to yield deeper insight into an experiment or biological system. For microRNA sequencing, our unique XPloreRNA™ App is integrated into the data analysis to facilitate gene ontology mediated assessment of biological significance. This NGS platform complements our existing bioinformatics and experimental services business, built on extensive experience gathered from the profiling of almost 30.000 clinical samples on our microarray and qPCR platforms within a highly controlled laboratory infrastructure.
In this presentation we will provide an overview of the bioinformatics platform and present some specific examples of its application to real NGS datasets as well as results from quality control studies using test data.

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