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limmaGUI A Point-and-Click Interface for cDNA Microarray Analysis

limmaGUI A Point-and-Click Interface for cDNA Microarray Analysis. James Wettenhall and Gordon Smyth Division of Genetics and Bioinformatics Walter and Eliza Hall Institute of Medical Research. limma, limmaGUI and affylmGUI. limma : linear models for microarrays by Gordon Smyth

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limmaGUI A Point-and-Click Interface for cDNA Microarray Analysis

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  1. limmaGUIA Point-and-Click Interface for cDNA Microarray Analysis James Wettenhall and Gordon Smyth Division of Genetics and Bioinformatics Walter and Eliza Hall Institute of Medical Research

  2. limma, limmaGUI and affylmGUI • limma : linear models for microarrays • by Gordon Smyth • Also contains many useful functions specifically for cDNA microarrays • limmaGUI : A Graphical User Interface for cDNA analysis with limma. • affylmGUI :A Graphical User Interface for Affymetrix analysis with limma.

  3. R, G, M and A • Rf = Red Foreground Intensity • Rb = Red Background Intensity • R = Rf - Rb • Gf = Green Foreground Intensity • Gb = Green Background Intensity • G = Gf - Gb

  4. R G Plot for ApoAI Slide 1

  5. log2(R) log2(G) Plot for ApoAI Slide 1

  6. M and A • Log Ratio : M (“Minus”) = log2(R/G) = log2R – log2G • Average Log Intensity : A (“Add”) = log2(RG)1/2 = (1/2)(log2R + log2G)

  7. M A Plot for ApoAI Slide 1

  8. Normalized M A Plot for ApoAI Slide 1

  9. M and A Have Nicer Distributions

  10. Linear Models in Microarrays Suppose for one gene, we have: M1 = log2(R1/G1) = log2(4/32) = -3 M2 = log2(R2/G2) = log2(15/2) = 2.9

  11. Linear Models in Microarrays • This linear model has oneparameter,MKO-WTto be estimated for each gene. • This parameter was estimated using a simple (weighted) average. • A factor of (-1) was used for the dye-swap.

  12. Linear Models in Microarrays What about confidence statistics? • As M1 is close to -M2 , we are confident in our estimate for MKO-WT so we expect: • A low p-value • A high B statistic (log-odds of D.E.) • A largenegative moderated t statistic (because this gene is down-regulated).

  13. Linear Models in Microarrays • What makes this a LINEAR model? • Let E{} be the expected value of . • We have : E{M1} = (1) MKO-WT E{M2} = (-1) MKO-WT • A linearrelationship. • The design matrix is :

  14. limma and limmaGUI • http://bioinf.wehi.edu.au/limma • Documentation is available after installing the package, by typing “help.start()” in R, clicking on “packages” and then clicking on “limma”. • http://bioinf.wehi.edu.au/limmaGUI • Documentation is available online. • Example data sets are available online.

  15. Swirl Zebrafish Example • http://bioinf.wehi.edu.au/limmaGUI/Doc/Swirl/

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