BIN-EXPR-Multiple testing
Multiple Testing and Significance
(Multiple testing problem. Concepts, Bonferroni correction and FDR)
Abstract:
Searching for significant effects in high-throughput experiments changes the statistical odds of finding highly unusual outcomes. This needs to be properly corrected, especially in situations like expression analysis where we observe tens of thousands of measurements simultaneously and need to determine which ones should be followed up on.
Objectives:
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Outcomes:
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Deliverables:
Prerequisites:
This unit builds on material covered in the following prerequisite units:
Contents
Task:
- Read the introductory notes on multiple testing.
Self-evaluation
Notes
Further reading, links and resources
If in doubt, ask! If anything about this learning unit is not clear to you, do not proceed blindly but ask for clarification. Post your question on the course mailing list: others are likely to have similar problems. Or send an email to your instructor.
About ...
Author:
- Boris Steipe <boris.steipe@utoronto.ca>
Created:
- 2017-08-05
Modified:
- 2017-11-10
Version:
- 1.0
Version history:
- 1.0 First live version
- 0.1 First stub
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