1. Cleaver – Classification of Expression Array Version 1.0 Hongli Li Spring 2003 91.580 Computational Biology Computer Science Department UMASS Lowell

2. Cleaver http://classify.stanford.edu/index.html

3. Features Graphical and Text Output and Storage Take tab-delimited Text Input File GeneNameAttr1Attr2Attr3Attr4Attr5 Gene 1X11X12X13X14X15 Gene 2X21X22X23X24X25 Gene 3X31X32X33X34X35

4. Features (Cont.) Data Transformation  Column/Row Normalize  Row/Column Rank  Log Missing Values  Zero Fill  Average Over Genes  Average Over Arrays

5. Analysis Methods K-means Cluster  Euclidean Distance  Manhattan Distance  Correlation based  Variance Scaled  Covariance Scaled Principal Component Analysis Classification

6. K-means Cluster

7. PCA – Principal Component Analysis

8. Classification

9. Conclusion Easy to use Include common analysis methods The Data transformation is very good The more packages can be find in  http://ihome.cuhk.edu.hk/~b400559/arraysoft_mini ng_specific.html http://ihome.cuhk.edu.hk/~b400559/arraysoft_mini ng_specific.html