Difference between revisions of "Rosaceae"

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===== Normalization talk (10mins) ''Robert Schaffer''=====  
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==== Normalization talk (10mins) ''Robert Schaffer''====  
  
===== Introduce R/Bioconductor framework  (15+ mins do a tutorial 45mins→ 1hr)=====
+
==== Introduce Bioconductor/R framework  (15+ mins do a tutorial 45mins→ 1hr)====
 
=====Bioconductor=====
 
=====Bioconductor=====
 
*Bioconductor is an open source development software project
 
*Bioconductor is an open source development software project
 
*Provides tools for analysis and comprehension of genomic data
 
*Provides tools for analysis and comprehension of genomic data
 
*Extensively for Affymetrix and cDNA microarray technologies
 
*Extensively for Affymetrix and cDNA microarray technologies
 
 
*The project started in the autumn of 2001  
 
*The project started in the autumn of 2001  
 
 
*Includes 23 core collaborating developers
 
*Includes 23 core collaborating developers
  
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*To develop a computing environment for both biologists and statisticians
 
*To develop a computing environment for both biologists and statisticians
 
*Promote high-quality dynamic documentation and reproducible research  
 
*Promote high-quality dynamic documentation and reproducible research  
 
  
 
<table class=document-code><tr><td>
 
<table class=document-code><tr><td>

Revision as of 10:15, 13 March 2006

Microarray analysis workshop

Time schedule: 8:30 - 10:30am, 11-12:30am (3.5 hours)


Workflow

Introduction to microarray analysis (10mins)

Normalization talk (10mins) Robert Schaffer

Introduce Bioconductor/R framework (15+ mins do a tutorial 45mins→ 1hr)

Bioconductor
  • Bioconductor is an open source development software project
  • Provides tools for analysis and comprehension of genomic data
  • Extensively for Affymetrix and cDNA microarray technologies
  • The project started in the autumn of 2001
  • Includes 23 core collaborating developers
Bioconductor Goals

The broad goals of the project are:

  • To enable sound and powerful statistical analyses in genomics
  • To provide a computing platform that allows the rapid design and deployment of high-quality software
  • To develop a computing environment for both biologists and statisticians
  • Promote high-quality dynamic documentation and reproducible research

+R tasklist

    • tasks available from web which utilze example data available in R - object assignment, subsetting, plotting, mathematical functions, sorting etc (20 tasks?)
  • Usage/interaction within environment
  • Bioconductor resources/vignettes(including downloading)
  • Bioconductor basics (any resources for limma out there?)
Brief about Limma (10-15 mins)
  • Essentially t-statistics for each spot/gene
  • Uses between gene information in moderated t-statistics
  • Computationally fast/robust
  • Handles missing information/use defined flag information
  • benefits/limitations?
  • FDR control? → ranking better than selecting cutoff
Analysis script (1+hours)

+Workshop.R


Scratch pad

  • A flow diagram for analysis
  • Recap of cDNA microarrays (slide 3)
  • Microarray data issues (slide 4)
  • Microarray data issues (continued)
    • Large amount of data (GPR/JPEG file size)
    • Subjective
    • Need a log of what was done so someone else can quickly reroduce the results
    • → Reproducible research (someone else can understand/reproduce the results) (McGintys talk)
  • Analysis process
  • R resources/contributed guides (including downloading)
  • R tutorial of basics (objects/indexing/functions)