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SUMMARY:Bootstrapping cluster analysis: assessing the reliability of concl
 usions - Jules Griffin ( Department of Biochemistry\, University of Cambri
 dge)
DTSTART:20070727T130000Z
DTEND:20070727T140000Z
UID:TALK7714@talks.cam.ac.uk
CONTACT:Dr N Karp
DESCRIPTION:Presenting the paper by  Kerr MK & Churchill GA\nPROCEEDINGS O
 F THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 98 (16)
 : 8961-8965 JUL 31 2001\n\n(paper available through ISI Web of knowledge)\
 n\nAbstract:We introduce a general technique for making statistical infere
 nce from clustering tools applied to gene expression microarray data. The 
 approach utilizes an analysis of variance model to achieve normalization a
 nd estimate differential expression of genes across multiple conditions. S
 tatistical inference is based on the application of a randomization techni
 que\, bootstrapping. Bootstrapping has previously been used to obtain conf
 idence intervals for estimates of differential expression for individual g
 enes. Here we apply bootstrapping to assess the stability of results from 
 a cluster analysis. We illustrate the technique with a publicly available 
 data set and draw conclusions about the reliability of clustering results 
 in light of variation in the data. The bootstrapping procedure relies on e
 xperimental replication. We discuss the implications of replication and go
 od design in microarray experiments.\n\n
LOCATION:Meeting room 1 cambridge system biology centre
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