Linear models for Microarray analysis

Overview of Limma package for R

• Fits a linear model for each spot (gene)
• An open source software package for the R programming environment
• Focus on normalization and statistical analysis of cDNA microarray gene expression data
• OOP environment for handling information in a microarray experiment
• Statistical analysis approach can be used for Affymetrix microarray experiments

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Origin

• Written and maintained by Gordon Smyth with contributions From WEHI, Melbourne, Australia
• Software made public at the Australian Genstat Conference, Perth, in Dec 2002
• Became available in the Bioconductor open source bioinformatics project April 2003
• Limma integrates with other Bioconductor software packages, affy, marray, using convert package
• Active development cycle

File:Limma versions.tiff

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Object orintated programming environment

File:OOP.tiff

• uploading data into R automatically populates elements of RGList
  • R (Red foreground)
  • Rb (Red background)
  • G (Green foreground)
  • Gb (Green background)
  • genes (Spot annotation list)
  • weights (prior weights weights given to each spot)

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Scratchpad

• 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