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.

 

Additional Resources.

www.amaratunga.com

 

Meeting information

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.

 

Registration Information and registration fees

 

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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