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General Departmental Seminar Series

Multivariate Segmentation in the Analysis of
Transcription Tiling Array Data

Antonio Piccolboni, PhD
Affymetrix, Emeryville CA
Computational Systems Biology
Cluster Hire Candidate

Tuesday, March 27, 2007

Biotech Center
145 Henry Mall



Tiling DNA microarrays extend current microarray technology by probing
the non-repeat portion of a genome at regular intervals in an unbiased
fashion. A fundamental problem in the analysis of these data is the
detection of genomic regions that are differentially transcribed across
multiple conditions. We propose a linear time algorithm based on
segmentation techniques and linear modeling that can work at a user-selected false discovery rate. It also attains a four-fold sensitivity gain over the only competing algorithm when applied to a whole genome transcription data set spanning the embryonic development of Drosophila melanogaster.

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