Analyzing and Visualizing Expression Data with Spotfire

Deepak Kaushal1, Clayton W. Naeve1

1 St. Jude Children's Research Hospital, Memphis, Tennessee
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 7.9
DOI:  10.1002/0471250953.bi0709s7
Online Posting Date:  October, 2004
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Abstract

This unit assumes the reader is familiar with the Spotfire environment, has successfully installed Spotfire, and has uploaded and prepared data for analysis. It presents numerous methods for analyzing microarray data. Specifically, the first two protocols describe methods for identifying differentially expressed genes via the t‐test/ANOVA and the distinction calculation respectively. Another protocol discusses how to conduct a profile search. Additional protocols illustrate various clustering methods, such as hierarchical clustering, K‐means clustering, and principal components analysis. A protocol explaining coincidence testing allows the reader to compare the results from multiple clustering methods. Additional protocols demonstrate querying the Internet for information based on the microarray data, mathematically transforming data within Spotfire to generate new data columns, and exporting Spotfire visualizations.

     
 
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Table of Contents

  • Basic Protocol 1: Identification of Differentially Expressed Genes Using t‐test/ANOVA
  • Alternate Protocol 1: Identification of Differentially Expressed Genes using Distinction Calculation
  • Basic Protocol 2: Identification of Genes Similar to a Given Profile: The Profile Search
  • Support Protocol 1: Editing a Master Profile
  • Basic Protocol 3: Coincidence Testing
  • Basic Protocol 4: Hierarchical Clustering
  • Support Protocol 2: Adding a Column from Hierarchical Clustering
  • Alternate Protocol 2: Hierarchical Clustering on Keys
  • Basic Protocol 5: K‐Means Clustering
  • Basic Protocol 6: Principal Components Analysis
  • Support Protocol 3: Transposing Data in Spotfire Decision Site
  • Basic Protocol 7: Using Web Links to Query the Internet for Useful Information
  • Basic Protocol 8: Generating New Columns of Data in Spotfire
  • Basic Protocol 9: Exporting Spotfire Visualizations
  • Guidelines for Understanding Results
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
 
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Materials

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Figures

Videos

Literature Cited

Literature Cited
   Eisen, M.B., Spellman, P.T., Brown, P.O., and Botstein, D. 1998. Cluster analysis and display of genome‐wide expression patterns. Proc. Natl. Acad. Sci. U.S.A. 95:14863‐14868.
   Jolliffe, I.T. 1986. Springer Series in Statistics, 1986: Principal Component Analysis. Springer‐Verlag, New York.
   Kerr, M.K. and Churchill, G.A. 2001. Experimental design for gene expression microarrays. Biostatistics 2:183‐201.
   MacQueen, J. 1967. Some methods for classification and analysis of multivariate observations In Proceedings of the Fifth Berkeley Symposium on Mathematics, Statistics and Probability, Vol I. (L.M. Le Cam and J. Neyman, eds.) pp. 281‐297. University of California Press, Berkeley, Calif.
   Sankoff, D. and Kruskal, J.B. 1983. Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison. Addison‐Wesley Publishing, Reading, Mass.
   Tavazoie, S., Hughes, J.D., Campbell, M.J., Cho, R.J., Church, G.M. 1999. Systematic determination of genetic network architecture. Nat. Genet. 22:281‐285.
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