By Professor Gilbert Chu
ESI Special Topics,
January 2003
Citing URL - http://www.esi-topics.com/nhp/2003/january-03-GilbertChu.html
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Professor Gilbert Chu answers a few questions about this month's
new hot paper in the field of Multidisciplinary.
From
•>>January 2003
Field: Multidisciplinary
Article Title:
"Significance analysis of microarrays applied to the ionizing radiation response"
Authors: Tusher, VG;Tibshirani, R;Chu, G
Journal: PROC NAT ACAD SCI USA
Volume: 98
Page: 5116-5121
Year: APR 24 2001
* Stanford Univ, Dept Med, Ctr Clin Sci Res 1115, 269 Campus Dr, Stanford, CA 94305 USA.
* Stanford Univ, Dept Med, Ctr Clin Sci Res 1115, Stanford, CA 94305 USA.
* Stanford Univ, Dept Biochem, Ctr Clin Sci Res 1115, Stanford, CA 94305 USA.
* Stanford Univ, Dept Hlth Res & Policy, Stanford, CA 94305 USA.
* Stanford Univ, Dept Stat, Stanford, CA 94305 USA.
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 Why
do you think your paper is highly cited?
Microarrays can measure the expression of genes across the entire
genome, and the technology has found application throughout the
biological sciences. Methods are needed to determine the
significance of changes in expression detected
by microarrays. This
paper describes a robust method that meets this need. Many
investigators have used the method to analyze their own data, and
therefore have cited the paper.
Does
it describe a new discovery or a new methodology that's useful to
others?
The new method is called Significance Analysis of Microarrays
(SAM). It assigns a score to each gene on the basis of change in
gene expression between different states relative to the standard
deviation of repeated measurements. SAM uses permutations of the
repeated measurements to estimate the percentage of genes identified
by chance, the false discovery rate. The method is easy to use and
can be downloaded
as software from the web. Because of its accessibility, SAM has
become very useful to others.
What
were some of the circumstances that led you to do this research?
We were measuring the transcriptional response of cells to
ionizing radiation with the aim of identifying patients at high risk
for toxicity from radiation therapy. Very early on, we discovered
that we needed new tools for analyzing microarray data before we
could have any hope of addressing our original aim.
Could
you summarize the significance of your paper in layman's terms?
Microarrays offer great opportunities for discovery by generating
huge amounts of data. Apparent effects on gene transcription can be
discovered by sifting through this data.
However, this type of discovery can be akin to the discovery of
amazing coincidences unearthed by searches through huge amounts of
information on the internet. Biologists were finding effects in
microarray data, but they needed tools to determine whether these
effects might be coincidences due to
chance or real effects due to important biological mechanisms. SAM
provides statistical tools that help answer this question.
Gilbert Chu
Professor of Medicine and Biochemistry
Division of Oncology
Stanford University Medical Center
Stanford, CA, USA
Robert Tibshirani, Ph.D.
Professor of Health Research Policy and Statistics
Stanford University
Stanford, CA, USA
Virginia Goss Tusher ,
Ph.D.
Independent Scientific Consulting
Tiburon, CA, USA
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ESI Special Topics,
January 2003
Citing URL - http://www.esi-topics.com/nhp/2003/january-03-GilbertChu.html
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