spectral_cluster

spectral_cluster - Spectral clustering for microarray data...

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Unformatted text preview: Spectral clustering for microarray data Alvin Liang Grant Wang Cameron Wheeler 12 May 2005 Outline Introduction to spectral algorithm Application to Golub et al. leukemia data set Application to Devauchelle et al. arthritis data set Introduction to the spectral algorithm Two steps: Create hierarchical tree in top-down manner based on eigenvalues, eigenvectors Merges leaves in bottom-up fashion to create clusters based on objective function Informally, objective function maximizes: (similarity inside clusters) - (similarity outside clusters) You choose what similarity means Algorithm has been applied in other contexts (web search) Golub et al. data 38 training patients, 34 test patients Cluster into acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) They consider class discovery: What if you didnt know about the ALL/AML distinction? How would you find it? Their answer: clustering Their results Only 4 errors out of 34 using self- organizing maps, in two clusters (they used GENECLUSTER) How does spectral clustering do?...
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This note was uploaded on 11/11/2011 for the course BIO 7.344 taught by Professor Bobsauer during the Spring '08 term at MIT.

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spectral_cluster - Spectral clustering for microarray data...

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