GCB/CIS 535 Microarray Topics John Tobias November 3 rd, 2004.
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Transcript of GCB/CIS 535 Microarray Topics John Tobias November 3 rd, 2004.
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GCB/CIS 535Microarray Topics
John TobiasNovember 3rd, 2004
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Overview
•Experimental Design
•Technology
•Replicates
•Experimental Execution
•Data Processing
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Overview
•Experimental Design
•Technology
•Replicates
•Experimental Execution
•Data Processing
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Experimental Design
•Identify Critical Conditions
•Identify Critical Comparisons
•Minimize Conditions
•Maximize Replicates
•Consider conditional changes in cell type representation - Do you need laser capture?
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Pooling
•Benefits
•More RNA - avoid double amplification
•Caveats
•Learn information about the pool - may not apply to individuals
•A bad sample can have a broad effect
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Overview
•Experimental Design
•Technology
•Replicates
•Experimental Execution
•Data Processing
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Technology Choice
•One Color - Affymetrix
•Simplifies experimental design
•Robust manufacturing process
•Two Color - cDNA or long oligo spotted
•Lower per-array cost
•Custom arrays - for organism or application
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Design ExamplesOne Color Two ColorConditions
2
3
x3
or
x3
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Two Color ExamplesLoop
A
BC
D
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Two Color Examples Common Reference
A B C D
Ref
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Two Color Design Choices•Loop
•All pairwise comparisons are direct
•Expensive for several conditions
•Hard to add conditions
•Common Reference•Design remains simple for multiple
conditions
•All pairwise comparisons are indirect
•Choice of appropriate reference is tricky
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Overview
•Experimental Design
•Technology
•Replicates
•Experimental Execution
•Data Processing
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Replicates - you can’t have too
many•What is a replicate?
•Replicates add statistical power to your data
•How many you need depends on the variation inherent in your system
•You probably don’t need technical replicates
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Overview
•Experimental Design
•Technology
•Replicates
•Experimental Execution
•Data Processing
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Pilot Experiments•When to do them
•Known dysregulated genes can be confirmed
•Plan for how results will drive experimental design
•Verification of sample preparation protocol
•Pitfalls
•No reliable statistics to do meaningful discovery
•Often cannot be added to a dataset produced later
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Controlling Variation
•Avoiding Batch Effects
•Reagent Lots
•Incubators
•Animal Handling
•Time
•Affects all of the above
•Hard to “add replicates later if I need them”
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Overview
•Experimental Design
•Technology
•Replicates
•Experimental Execution
•Data Processing
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Affymetrix Terminology
AAAAAAA
Probe (PM)
Probe (MM)
Probe PairProbe Set
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Pixel (.dat file)
Affy Summarization Steps
Probe (.cel file)
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From Probes to Genes
•Affymetrix Microarray Suite v5 - “statistical”
•Model Based Choices:
•RMA - http://www.stat.berkeley.edu/~bolstad/RMAExpress/RMAExpress.html
•GC-RMA - http://www.bepress.com/jhubiostat/paper1/
•dChip (MBEI) - http://www.dchip.org/
•PLIER – Affymetrix (open source release)
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MAS5 vs. GCRMA
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R•The R Project for Statistical
Computing
•http://www.r-project.org/
•Bioconductor
•http://www.bioconductor.org/
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Contact Information
•Penn Bioinformatics Core - 13th Floor Blockley Hall
•John Tobias - 1314 - [email protected]
•Reserve Computers
•http://core.pcbi.upenn.edu/