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New Hot Paper Comments

By Rafael A. Irizarry

ESI Special Topics, July 2004
Citing URL - http://www.esi-topics.com/nhp/2004/july-04-RafaelIrizarry.html

Rafael A. Irizarry answers a few questions about this month's new hot paper in the field of Mathematics.


From •>>July 2004

Field: Mathematics
Article Title: Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Authors: Irizarry, RA;Hobbs, B;Collin, F;Beazer-Barclay, YD;Antonellis, KJ;Scherf, U;Speed, TP - see also
Journal: BIOSTATISTICS
Volume: 4
Page: 249-264
Year: APR 2003
* Johns Hopkins Univ, Dept Biostat, Baltimore, MD 21205 USA.
* Johns Hopkins Univ, Dept Biostat, Baltimore, MD 21205 USA.
* WEHI, Div Genet & Bioinformat, Melbourne, Vic, Australia.
* Gene Log Inc, Berkeley, CA USA.
* Gene Log Inc, Gaithersburg, MD USA.
* Univ Calif Berkeley, Dept Stat, Berkeley, CA 94720 USA.

This paper has also been named the Fast Breaking Paper in Mathematics for October 2004.

ST:  Why do you think your paper is highly cited?


“Affymetrix GeneChip microarrays is a tool developed for high throuput measurement of gene expression.”

This paper describes a methodology which improves the output of a highly used technology. We provide free open source software which users of this technology can download and implement. Researchers using our methodology and software usually cite this reference.

ST:  Does it describe a new discovery or new methodology that's useful to others?

It describes a methodolgy that is useful to the users of the Affymetrix GeneChip arrays. These arrays are widely used by researchers interested in measuring gene expression from biological samples of interest.

ST:  Could you summarize the significance of your paper in layman's terms?

The Affymetrix GeneChip microarray is a tool developed for high-throughput measurement of gene expression. A typical microarray can measure expression for more then 10,000 genes simultaneously. The raw data obtained from this technology needs various levels of pre-processing before one finally arrives at one measurement of expression for each gene on each array. The methodolgy we have developed and described in this article greatly improves the precision of the default algorithms provided by Affymetrix. Our methods are based on empirically motivated statistical models.

ST:  How did you become involved in this research?

Several of my collaborators are clinicians or lab scientists who are using the Affymetrix technology. I was dissatisfied with the quality of the data these collaborators were obtaining with the default—and other existing alternative—algorithms. In the fall of 2001, I started a collaboration with Terry Speed, who was also interested in this problem. By early 2002 we had developed an initial version of our methodology along with the software to implement its use.End

Rafael A. Irizarry
Associate Professor
Department of Biostatistics
Johns Hopkins Bloomberg School of Public Health
Baltimore, MD, USA

ESI Special Topics, July 2004
Citing URL - http://www.esi-topics.com/nhp/2004/july-04-RafaelIrizarry.html

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