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Introduction Methodology The IsoGeneGUI Package Availability
IsoGeneGUI: a graphical user interface foranalyzing dose-response studies in microarray
experiments
Setia Pramana
Interuniversity Institute for Biostatistics and StatisticalBioinformatics, Universiteit Hasselt, Diepenbeek, Belgium
Introduction Methodology The IsoGeneGUI Package Availability
Outline
IntroductionDose-response StudiesIsoGene PackageIsoGeneGUI Package
MethodologyTest Statistics for Trend TestAsymptotic E2
PermutationSignificance Analysis of Microarray (SAM)
The IsoGeneGUI PackageMenuData ExplorationPermutationLikelihood Ratio Test E2 AnalysisSAMPlots
Availability
Introduction Methodology The IsoGeneGUI Package Availability
Dose-response studies
The fundamental objective of drug development.
Aims: find dose or range of dose that efficacious and safe.
Introduction Methodology The IsoGeneGUI Package Availability
Dose-response studies
To carry out the analysis of dose-response microarrayexperiments, Lin et al. (2007) discused the following teststatistics which take into account the order restriction of meanswith respect to the increasing doses:
Williams (Williams, 1971, 1972)
Marcus (Marcus, 1976)
the likelihood ratio test (E2) (Bartholomew 1961 , Barlow etal. 1972, and Robertson et al. 1988)
M statistic (Hu et al. 2005)
Modified M statistic (Lin et al. 2007)
Introduction Methodology The IsoGeneGUI Package Availability
IsoGene Package
An R package that carries out analysis of dose-responsemicroarray experiments discussed by Lin et.al 2007.
The inference is based on resampling methods, bothpermutations (Ge et al., 2003) and the SignificanceAnalysis of Microarrays (SAM, Tusher et al., 2001).
To control the False Discovery Rate (FDR) the BenjaminiHochberg (BH) procedure is implemented.
Available at: http://cran.ii.uib.no/web/packages/IsoGene/
Introduction Methodology The IsoGeneGUI Package Availability
IsoGeneGUI Package
The interface of the IsoGene package.
A graphical user interface based on R-tcl/tk package(Dalgaard, 2001).
A menu based package and data analysis can beperformed simply by selecting options from the menus ofthe package
Produces some default graphical displays as well asuser-defined graphical output.
Introduction Methodology The IsoGeneGUI Package Availability
Test Statistics for Trend Test
Test statistic Formula
Likelihood Ratio E201 =
∑
ij (yij−µ)2−
∑
ij (yij−µ⋆
i )2
∑
ij (yij−µ)2
Test (LRT)
Williams t = (µ⋆
K − y0)/√
2 ×
∑Ki=0
∑nij=1(yij − µi )2/(ni (n − K ))
Marcus t = (µ⋆
K − µ⋆
0 )/√
2 ×
∑Ki=0
∑nij=1(yij − µi )2/(ni (n − K ))
M M = (µ⋆
K − µ⋆
0 )/√
∑Ki=0
∑nij=1(yij − µ⋆
i )2/(n − K )
Modified M (M’) M′ = (µ⋆
K − µ⋆
0 )√
∑Ki=0
∑nij=1(yij − µ⋆
i )2/(n − I)
Introduction Methodology The IsoGeneGUI Package Availability
Analysis
Three analyses can be performed in the package:
E201 using its null distribution.
The five test statistics using permutations.
The Significance Analysis of Microarrays.
Introduction Methodology The IsoGeneGUI Package Availability
Likelihood ratio test (E2)
The null distribution of E2 test statistic is given by
P[E201(v) ≥ c] =
k∑
l=1
P(l , k ; w)P[B(l−1)/2,(v+k−l)/2 ≥ c], (1)
where l = 1, , 2, ..., k , v = N − k , Ba,b is a beta variable withparameters a and b, w is the weight vector through the levelprobabilities P(l , k ; w) as defined in Robertson et al. 1988.
Introduction Methodology The IsoGeneGUI Package Availability
Permutation
By permuting the labels of arrays randomly, the permutationtest statistics of m genes are re-calculated and obtain thepermutation matrix T :
T =
t11 t11 . . . t1B
t21 c22 . . . t2B...
...tm1 tm2 . . . tmB
(2)
where B is the number of permutations and each element tib ofmatrix T is the test statistic for the i-th gene in the b-thpermutation.The raw p-values:
Pi =#(b : |tib| ≥ |ti |)
B − 1(3)
where ti is the observed test statistic for gene i (Ge et al. 2003).
Introduction Methodology The IsoGeneGUI Package Availability
Significance Analysis of Dose-response MicroarrayData (SAM, Tusher et al., 2001)
The generic algorithm of SAM discussed by Chu et al.(2001) is implemented in this package.The SAM regularized test statistic:
For the t-type test statistics (i.e., Williams, Marcus, the M,and the M ′), a fudge factor is added in the standard error ofthe mean difference. For example:
M ′SAM =µ
⋆
K − µ⋆
0
s′ + s0, (4)
where s0 is the fudge factor.For the F -type test statistic, such as E2
01, is defined by
E2SAM01 =
√
σ2H0
− σ2H1
√
σ2H0
+ s0
. (5)
Introduction Methodology The IsoGeneGUI Package Availability
The IsoGeneGUI
Introduction Methodology The IsoGeneGUI Package Availability
The IsoGeneGUI: Menu
FileThis menu is used for loading and showing the data.Sub-menus:
Open DataR workspace (*.RData files)Excel or text file (*.xls or *.txt files)
Show DataExit
AnalysisThis is the main menu where the analyses are performed.Sub-menus:
Set seedLikelihood Ratio Test E2 AnalysisPermutation AnalysisSignificant Analysis of Microarrays (SAM)
SAM PermutationSAM Analysis
Introduction Methodology The IsoGeneGUI Package Availability
The IsoGeneGUI: Menu
PlotsBesides plots that can be produced in each the analysisdialog box, the package also provides extra plots:
IsoPlotPermutation PlotSAM Plot
Plot of FDR vs. DeltaPlot of number of significant genes vs. DeltaPlot of number of False Positive vs. Delta
User defined scatter plot
Help
IsoGene HelpIsoGeneGUI Manual and ExamplesAbout
Introduction Methodology The IsoGeneGUI Package Availability
Data Exploration
The IsoPlot dialog box
Introduction Methodology The IsoGeneGUI Package Availability
Data Exploration
The Isotonic regression plots The summary statistic
Introduction Methodology The IsoGeneGUI Package Availability
Likelihood Ratio Test E2 Analysis
The dialog box
Introduction Methodology The IsoGeneGUI Package Availability
Likelihood Ratio Test E2 Analysis
Output: List significant genes
Can be saved as R object or/and an excel file.
Introduction Methodology The IsoGeneGUI Package Availability
Likelihood Ratio Test E2 Analysis
Output: Fold change vs. E2 plot
Can be copied into clipboard and be saved as different imagetypes.
Introduction Methodology The IsoGeneGUI Package Availability
Permutation
Introduction Methodology The IsoGeneGUI Package Availability
Permutation
The output:
Result for all genes.
list of significant genes using the selected statistic(s).
Graphical displays.
Introduction Methodology The IsoGeneGUI Package Availability
Significance Analysis of Microarrays (SAM)
The SAM permutation dialog box
Introduction Methodology The IsoGeneGUI Package Availability
Significance Analysis of Microarrays (SAM)
Introduction Methodology The IsoGeneGUI Package Availability
Significance Analysis of Microarrays (SAM)
Output: Delta table
Introduction Methodology The IsoGeneGUI Package Availability
Plots
Permutation p-values plot
Introduction Methodology The IsoGeneGUI Package Availability
Plots
User Defined Scatter Plot
Introduction Methodology The IsoGeneGUI Package Availability
Help
Html help with screenshots
Introduction Methodology The IsoGeneGUI Package Availability
Infobox
Provides information about the data (availability and summary)and the result summary of the last performed analyses.
Introduction Methodology The IsoGeneGUI Package Availability
Availability
R-forge site:https://r-forge.r-project.org/projects/isogenegui/
To install: install.packages(”IsoGeneGUI”,repos=”http://R-Forge.R-project.org”)
The full user manual and example data will be soonavailable at: http://www.censtat.uhasselt.be/software/
Plan to be submited to Bioconductor
Introduction Methodology The IsoGeneGUI Package Availability
Selected References
Barlow, R.E., Bartholomew, D.J., Bremner, M.J. and Brunk, H.D.(1972) Statistical Inference Under Order Restriction, New York:Wiley.
Benjamini, Y. and Hochberg, Y. (1995) Controlling the falsediscovery rate: a practical and powerful approach to multipletesting, J. R. Statist. Soc. B, 57, 289-300.
Lin, Dan, Shkedy, Ziv, Yekutieli, Dani, Burzykowski, Tomasz,Gohlmann, Hinrich, De Bondt, An, Perera, Tim, Geerts, Tamaraand Bijnens, Luc.(2007) Testing for Trends in Dose-ResponseMicroarray Experiments: A Comparison of Several TestingProcedures, Multiplicity and Resampling-Based Inference,Statistical Applications in Genetics and Molecular Biology: Vol. 6: Iss. 1, Article 26.
Robertson, T., Wright, F.T. and Dykstra, R.L. (1988), OrderRestricted Statistical Inference, Wiley.
Introduction Methodology The IsoGeneGUI Package Availability
Thank you for your attention...
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