Monday, April 02, 2001

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GenomeWeb Researchers Attempt to Defuse the Microarray Data Minefield
"One of the biggest pitfalls in analyzing microarray data is the process of normalizing gene expression levels across two or more chips, or removing systematic variation between the chips when comparing different experiments, researchers have said.

“It's the same as if you are pointing a telescope into deep space and measuring how bright a star is,” said Nat Goodman, senior vice president of the bioinformatics consulting firm 3rd Millennium in Cambridge, Mass. “If you are comparing data from two different telescopes, or from the same telescope on different nights, one clear and one cloudy, you have to take that into account.”

“What's striking in the microarray arena,” Goodman noted, “is that people have simply ignored this issue.”"

redux [03.28.01]
BioMedNet New consortium to put microarray data into your hands
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"Leaders of an effort to standardize and centralize gene expression data on tumor samples today described their vision for an international non-profit consortium to make such microarray data available to all researchers. The non-governmental project aims to increase the rate of discovery and improve patient care, said Jeffrey Trent, scientific director of the National Human Genome Research Institute speaking at the American Association for Cancer Research conference in New Orleans."

redux [02.05.01]
Scientific American Shrinking to Enormity
"With each successive generation of microarray technology, the size of the probe spots shrinks, the number of genes per chip rises, and biologists' schemes for using the devices swell in grandeur. "We can now put over 60 million probes on a single glass wafer," Fodor says excitedly. He figures the entire human genome will fit on 200 to 300 wafers. And in fact, in September, Affymetrix spun off Perlegen, a subsidiary that plans to use microarrays to sequence, from scratch, the genomes contained in both chromosomes of 50 people to detect the subtle variations both within and among them. "In these patterns we will find the signature of human evolution. The potential for scientific discovery," Fodor boasts, "is fantastic."

So is the potential for confusion and error, Young and others caution."

[via bioinformatics.org]

The Scientist Microarrays Beyond Reach
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"Using the subheading "Microarray tools open genomes to discoverers" in the Jan. 22 Hot Papers article1 is much like telling a group of kindergartners: "Any of you can become the president of the United States." The fact is most of them will never be the president no matter how hard they try. Microarrays are excellent tools, but their exorbitant price makes them beyond the reach of most researchers. The few papers that have been published so far using the "chips" came from either rich labs or labs that have industrial/proprietary connections.

I don't think the microarray hot papers of today will remain hot for long. They were neither conceptually novel nor hard to do; they simply represent "proof of concept" or application of a great but easy technology."

redux [05.24.00]
Nature One-stop shop for microarray data
"With the advent of DNA microarray and 'chip' technologies...gene expression in an organism can be examined on a genomic scale, allowing the transcription levels of many genes to be measured simultaneously2. For instance, we can study the effects of a compound (such as a drug) on the level of expression of many genes...With gene expression, context is everything: without it, the information is meaningless. For example, the precise stage of a tumour sample could have a crucial bearing on the interpretation of expression measurements. This context can be infinitely detailed, and it is this detail that must be captured in gene-expression studies.

The bioinformatics underlying the management of these huge volumes of data are crucial if any sense is to be made of gene-expression experiments. A single microarray experiment looking at 40,000 genes from 10 different samples, under 20 different conditions, produces at least 8,000,000 pieces of information."

"It is time to create a public repository for microarray data, with standardized annotation (see Box 2, overleaf). But this is a complex and ambitious project, and is one of the biggest challenges that bioinformatics has yet faced. Major difficulties stem from the detail required to describe the conditions of an experiment, and the relative and imprecise nature of measurements of expression levels. The potentially huge volume of data only adds to these difficulties. However, it is this very complexity that makes an organized repository necessary.

Important tasks to be undertaken include: (1) agreement on the essential information that should be reported for a microarray experiment; (2) definition of ontologies and an extensible, structured document format to capture these data and their semantics; (3) production of a database to store these documents; and (4) development of tools for searching documents in a database and using the semantic context to allow comparisons and sophisticated queries."