GENOMICS
to integrate genomics data and clinical data. Jonathan Sheldon, director of translational medicine at IDBS, adds that, ideally, technologies within genomics like sequencing, gene expression, genome-wide association, methylation, copy number variation, which are all routinely applied to the same system, should be layered on top of each other and presented to the scientist for more effective interpretation.
Visualisation of array comparative genomic hybridisation (aCGH) expression data using CytoSure Interpret from Oxford Gene Technology
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Another informatics bottleneck that Mounts identifies is linking results data to other sample attributes and providing the information to a broad array of scientists in an intuitive way. Pfizer is using Genedata Expressionist and other informatics platforms to provide an interface for researchers to access and analyse disparate genomic data types. Intuitive presentation of data is something
that Ruth Burton, product manager clinical solutions at Oxford Gene Technology (OGT), also considers vital. OGT provides microarray products and services and Burton comments: ‘The challenge is going from a tiff image of a microarray to having data that people can work with, especially in a cytogenetics lab where researchers may be less familiar with microarray analysis. Considering the number of data points involved, it is not a trivial step to go from the image to the results data.’ OGT’s CytoSure Interpret software is used
to analyse the data generated from CytoSure microarrays, providing an overview of the genomic locations where signal intensity differs between sample and control DNA.
Only a piece of the puzzle Of course, genomics is not the be all and end all when it comes to investigating human physiology
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and a lot of institutes are trying to link the data generated by genomics with that of other omics technologies as well as clinical data. Trish Meek of Thermo Fisher Scientific comments: ‘When genomics is paired with proteomics, we can gain a real understanding of the human body.’ Thermo Fisher Scientific’s Nautilus LIMS
supports configurable sample and aliquot hierarchies to allow laboratories to tailor the sample structure to reflect the way they work. Information can then be referenced at each level in the hierarchy, enabling laboratories to track and maintain all of their sample data. One of the goals of the Molecular Genomic
Core of the University of Texas Medical Branch, for implementing GenoLogics’ Geneus platform to manage gene expression data, was so that clinical data could be integrated with basic science data. ‘Traditionally, basic research has been isolated from the clinics,’ says Dr Russ Carmical at the Core. ‘To gather more information and integrate that with other areas, like proteomics and metabolomics and health outcomes for the patient, is unmanageable without the data management capabilities of Geneus. We have a limited view when we just look at the gene expression data. Now you can take a larger view.’ IDBS’s InforSense suite is also a suitable tool
SCIENTIFIC COMPUTING WORLD AUGUST/SEPTEMBER 2010
Where next for next-gen? ‘An important point about his whole area is that it is rapidly changing,’ states Sheldon. ‘It’s evolving at such a pace that there has to be software that can cope.’ Sheldon also argues that, with regards to next- generation sequencing, the beauty of it is that it could give some uniformity to bioinformatics. In addition to sequencing genomes, it can be used to carry out SNP detection and whole transcriptome profiling – sequencing can give an idea of expression profiles instead of being reliant on microarray technology. ‘Gene sequences become the currency, if you like, of all these different genomic technologies,’ he says. ‘Sequence data as a uniform currency across all these techniques will make the modelling of the data much more straightforward.’ However, Johnson of EdgeBio warns that as
the cost of next-generation sequencing continues to fall, the danger is that everyone starts doing it their own way and the bioinformatics becomes even more non-standardised. Companies that don’t have the capabilities of large genome centres tend to do whatever they can to get an answer. It’s a big educational issue within the community to help people to try to use standardised tools.’ Next-gen sequencing is still too expensive
to be a widely-used genomics tool – the $1,000 genome is generally considered the holy grail, in terms of a price for which next-gen sequencing could begin to have clinical applications. ‘One of the things I hear, almost on a daily
basis, is that sequencing is almost free now,’ says Johnson. ‘That’s hard to see when there is a lot of capital expenditure, such as the sequencing machines, the staff, the project management, the bioinformatics, the compute infrastructure, etc. The cost of the reagents for sequencing is dropping significantly – the cost of reagents for Applied Biosystems’ SOLiD system to sequence an entire human genome is $6,000. What comes before and after is where people need to understand how to invest their time and money and those are significant challenges.’
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