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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

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

limma limmagui and affylmgui
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.
r g m and a
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
m and a
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)

linear models in microarrays
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

linear models in microarrays12
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.
linear models in microarrays13
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).

linear models in microarrays14
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 :
limma and limmagui
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.
swirl zebrafish example
Swirl Zebrafish Example
  • http://bioinf.wehi.edu.au/limmaGUI/Doc/Swirl/