San
Francisco Bay Area Chapter of the American Statistical Association.
Short Course
Monday May 3, 2010
Extracting Reliable Information
from Microarray Data: Strategies and Case
Studies
Dhammika Amaratunga
Johnson & Johnson Pharmaceutical Research & Development
A spate of recent
advances in genomics has significantly altered the way research is being
conducted in biology and medicine. It is now possible to investigate the
behavior of genes and proteins thousands at a time, a powerful resource for the
biological researcher. Of the current technologies, the most prominent is the
DNA microarray, which can be used to profile the expression patterns of tens of
thousands of genes simultaneously. How to properly analyze and interpret the
enormous amounts of data this technology generates remains a challenge as its
high dimensional structure, comprising many variables but few samples, renders
it vulnerable to over-fitting and over-interpretation. Generally, a
multi-faceted approach is likely to be the most effective at extracting
reliable information. Thus, for a standard well-designed comparative microarray
experiment, a fairly rigorous prescription for determining a gene expression
signature would include (1) a quality control step to settle any anomalies in the
data and to ensure that the data indeed carry a signal, (2) an individual gene
analysis to identify differentially expressed genes using a method that borrows
strength across genes to increase efficiency, (3) an analysis of gene sets to
identify affected biological processes and pathways, (4) an ensemble
classification procedure to identify similarities and/or dissimilarities
amongst the samples and the genes associated with any dissimilarities, (5) a
procedure to integrate concomitant data to assess concurrence of findings. This
course will introduce the issues underlying microarray data analysis and will
use actual case studies to review this multi-faceted approach.
Speaker
Biography
Dhammika Amaratunga is Senior Research
Fellow in Nonclinical Biostatistics at Johnson & Johnson Pharmaceutical
Research & Development. He has been involved in microarray data analysis
since 1997, the early days of microarrays. He and his team have numerous publications, including a
book, and they have also given numerous presentations and courses on this
topic. He has a B.Sc. from the University of Colombo, Sri Lanka, and a Ph.D. in
Statistics from Princeton University, where under the guidance of John Tukey he
learned the importance of careful exploratory data analysis.
Monday May 3, 2010
Checkin begins at 1:00
Course is 1:30 pm until 5:00
The
lecture room and facilities are
generously provided on-site at Genentech.
Seating
is limited, and advance registration is required. Registration closes on Friday
April 16, 2010.
To
register, please send an email to sfASAshortcourse@gmail.com (not
case sensitive) with your name and affiliation (as you would like it to appear
on your name card), your preferred email and contact information.
A
check, payable to “the ASA San Francisco Bay Area Chapter”, for the
registration fees (either $10.00 for Chapter members or $20.00 for non-members
of the Chapter) may be sent to
Anthony B. An, Ph.D.
SAS Institute Inc.
One Montgomery Street, 34th Floor
San Francisco, CA 94104
Tel: (415) 421-2227 Ext. 51463
Fax: (415) 421-1213
The
directions, transportation (BART, CALTRAIN), and parking instructions will be
emailed approximately two weeks prior to the meeting itself.
Bay
Area Chapter Leadership:
:
http://www.sfasa.org/chapinfo.htm#Officers
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