Transcript Slide 1

Data Analysis:
General Workflow &
Analysis Options
Duke Microarray Core Facility
Zhengzheng Wei
Nov. 2006
Overall Workflow and Analysis
Options
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Normalization (Lowess, RMA, MAS5, Quantile etc.)
Outlier Sample Removal (unsupervised hierarchical clustering, PCA)
Quality Control Filtering (Filter on Flag, Expression, Error etc.)
Gene Selection (ANOVA, Fold Change, SAM, Golub Method, Fisher
Exact Test, Condition Correlation etc.)
Clustering (unsupervised hierarchical clustering, supervised hierarchical
clustering, k-means clustering)
Gene annotations, Genelist Correlation, Venn Diagram For Genelists
Gene Ontology Analysis (GATHER, GeneSpring Gene Ontology)
Class Prediction (Support Vector Machine, K-nearest neighbor, PAM)
Pathway Analysis (MetaCore, KEGG Pathways)
Web hosting of Experiment Data
Principle Component Analysis
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ANOVA: Analysis of Variance
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Pairwise comparison: Volcano
Plot (ANOVA + Fold Change)
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Venn Diagram: Union and
intersection of Genelists
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Unsupervised Hierarchical Clustering
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Supervised Hierarchical Clustering
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K-Means Clustering
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Scatter plot
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Class Prediction: SVM
(Support Vector Machine)
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M argin
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control
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Class Prediction: PAM (Prediction
Analysis for Microarrays )
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Gene Annotations
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Gene Ontology: GATHER
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Gene Ontology: Genespring (1)
Table with P-value
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Next
Gene Ontology: Genespring
(2) Pie Chart
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Next
Gene Ontology: Genespring
(3) split window view
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Web Page Hosting of
Expression Data
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