Monday, February 2, 2009

Next Gen Laboratory Software Systems for Core Facilities

Do you have a core lab? Considering adding Next Generation DNA sequencing capacity to your lab? Then you will be interested in visiting our both and checking out our poster at the annual Association for Biomolecular Research Facilities (ABRF) meeting next week in Memphis TN. We'll be at booth 408, and presenting poster number V27-S1.

Poster Abstract

Throughout the past year, as next generation sequencing (NGS) technologies have emerged in the marketplace, their promise of what can be done with massive amounts of sequence data has been tempered with the reality that performing experiments and working with the data is extremely challenging. As core labs contemplate acquiring NGS technologies, they must consider how the new technologies will affect their current and future operations. The old model of collecting and delivering data is likely to change to one where the core lab becomes an active participant in advising and helping clients set up experiments and analyze the data. However, while many labs want to utilize NGS, few have the Information Technology (IT) infrastructures and procedures in place to successfully make use of these systems.

In the case of gene expression, NGS technologies are being evaluated as complementary or replacement technologies for microarrays. Assays like RNA-Seq and tag profiling, that focus on measuring relative gene expression, require that researchers and core labs must puzzle through a diverse collection of early version algorithms that are combined into complicated workflows with many steps producing complicated file formats. Command line tools such as MAQ, SOAP, MapReads, and BWA, have specialized requirements for formatted input and output and leave researchers with large data files that still require additional processing and formatting for tertiary analyses. Moreover, once reads are aligned, datasets need to be visualized and further refined for additional comparative analysis. We present solutions to these challenges by showing results from a complete workflow system that includes data collection, processing, and analysis for RNA-seq suited for the core laboratory.

In the poster we'll walk through the laboratory and data analysis issues one needs to think about to perform a two cell expression comparison with RNA-Seq. Below is a snippet from the poster. I'll post the full presentation when I return.

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