STATISTICS SEMINAR SERIES :: Detecting Differential Expression for Microarray Time Course Data

Event Details
  • Date/Time:
    • Thursday September 15, 2005
      11:00 am - 12:00 am
  • Location: Executive Classroom #228
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    N/A
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Contact
Barbara Christopher
Industrial and Systems Engineering
Contact Barbara Christopher
404.385.3102
Summaries

Summary Sentence: STATISTICS SEMINAR SERIES :: Detecting Differential Expression for Microarray Time Course Data

Full Summary: STATISTICS SEMINAR SERIES :: Detecting Differential Expression for Microarray Time Course Data

Among the first microarray experiments were those measuring expression over time, and time course experiments remain common. Most methods to analyze time course data attempt to group genes sharing similar temporal profiles within a single biological condition. However, with time course data in multiple conditions, a main goal is to identify differential expression patterns over time. I will present a Hidden Markov modeling approach designed specifically to address this question. Simulation studies show a substantial increase in sensitivity without an increase in the false discovery rate when compared to a marginal analysis at each time point. Results from three case studies will be discussed.

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Status
  • Created By: Barbara Christopher
  • Workflow Status: Published
  • Created On: Oct 8, 2010 - 7:38am
  • Last Updated: Oct 7, 2016 - 9:52pm