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Utilizing Lowess Method for Gene-Chip Analysis and Hierarchical Clustering

Explore the use of Lowess method and hierarchical clustering for correcting systematic bias in microarray analysis. Understand how to group similar genes and samples based on expression profiles. Discover gene functions and disease expression profiles.

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Utilizing Lowess Method for Gene-Chip Analysis and Hierarchical Clustering

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  1. Image from Gene-Chips (Micorrrays)

  2. Statistics for microarray analysis (SMA) • http://www.stat.berkeley.edu/users/terry/zarray/Software/smacode.html • Method: Lowess • Goal: adjust systematic bias • Assumption: changes roughly symmetric at all intensities within the region considered

  3. Hierarchical clustering • Technically, Eisen uses average-link agglomerative hierarchical clustering. • Similarity between genes is measured using a Pearson correlation coefficient. • Where to download the software: • http://rana.lbl.gov/EisenSoftware.htm

  4. Why cluster? • Place genes with similar expression profiles into clusters. • What is the gene’s function? • Place experiments / samples with similar expression profiles into clusters. • What is the expression profile of a particular disease or phenotype?

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