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

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Presentation transcript:

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

Cleaver

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

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

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

K-means Cluster

PCA – Principal Component Analysis

Classification

Conclusion Easy to use Include common analysis methods The Data transformation is very good The more packages can be find in  ng_specific.html ng_specific.html