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Activity Number:
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487
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Type:
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Contributed
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Date/Time:
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Thursday, August 7, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #301165 |
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Title:
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Statistical Methods for the Analysis of RNAi Screens
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Author(s):
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Imola K. Fodor*+ and William F. Forrest
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Companies:
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Genentech, Inc. and Genentech, Inc.
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Address:
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1 DNA Way, South San Francisco, CA, 94080-4990,
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Keywords:
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RNAi ; siRNA ; high throughput screening ; pathway ; normalization ; mixed-effects model
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Abstract:
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By selectively turning off one gene at a time, cell-based RNA interference (RNAi) screens provide an efficient means to investigate the genes involved in biological pathways of interest. This relatively new technology is currently being used both to conduct basic research on intracellular signaling pathways and to discover potential new drug targets. RNAi experiments typically consist of data from many microtiter plates, and statistical analyses can span from classical statistical tools (such as data transformations and mixed effects modeling) through areas of active statistical research (such as multiple testing frameworks). We describe some of the statistical challenges in RNAi experiments and illustrate some solutions through a case study.
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