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Analysis of Multiple Experiments TIGR Multiple Experiment Viewer (MeV) Joseph White DFCI January 24,2008
MeV ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Expression Matrix is a representation of data from multiple microarray experiments. Each element is a log ratio (usually log  2  (Cy5 / Cy3) )  Red indicates a  positive log ratio, i.e, Cy5 > Cy3  Green indicates a negative log ratio , i.e., Cy5 < Cy3  Black indicates a log ratio of zero, i. e.,  Cy5 and Cy3 are very  close in value  Gray indicates missing data   Exp 1 Exp 2 Exp 3 Exp 4 Exp 5 Exp 6 Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6
Expression Vectors ,[object Object],[object Object],Log2(cy5/cy3) -0.8 0.8 1.5 1.8 0.5 -1.3 -0.4 1.5
Expression Vectors As Points in ‘Expression Space’ Experiment 1 Experiment 2 Experiment 3 Similar Expression -0.8 -0.6 0.9 1.2 -0.3 1.3 -0.7 Exp 1 Exp 2 Exp 3 G1 G2 G3 G4 G5 -0.4 -0.4 -0.8 -0.8 -0.7 1.3 0.9 -0.6
Distance and Similarity  -the ability to calculate a distance (or similarity, it’s inverse) between two expression vectors is fundamental to clustering algorithms -distance between vectors is the basis upon which decisions are made when grouping similar patterns of expression -selection of a  distance metric  defines the concept of distance
Distance: a measure of similarity between genes. ,[object Object],[object Object],3.  Pearson correlation p 0 p 1 Exp 1 Exp 2 Exp 3 Exp 4 Exp 5 Exp 6 Gene A Gene B x 1A x 2A x 3A x 4A x 5A x 6A x 1B x 2B x 3B x 4B x 5B x 6B 6 ,[object Object],6
Distance is Defined by a Metric 4.2 1.4 -1.00 -0.90 Euclidean   Pearson(r*-1) Distance Metric : D D
Normal distribution X =  μ (mean of the distribution) σ  = std. deviation of the distribution
Current MeV Algorithms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Demos ,[object Object],[object Object],[object Object],[object Object],[object Object]
GeneChip Oncology Database
GeneChip Oncology Database
GCOD statistics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
MeV Team ,[object Object],[object Object],[object Object],[object Object]

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MeV: Joe White

  • 1. Analysis of Multiple Experiments TIGR Multiple Experiment Viewer (MeV) Joseph White DFCI January 24,2008
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  • 4. The Expression Matrix is a representation of data from multiple microarray experiments. Each element is a log ratio (usually log 2 (Cy5 / Cy3) ) Red indicates a positive log ratio, i.e, Cy5 > Cy3 Green indicates a negative log ratio , i.e., Cy5 < Cy3 Black indicates a log ratio of zero, i. e., Cy5 and Cy3 are very close in value Gray indicates missing data Exp 1 Exp 2 Exp 3 Exp 4 Exp 5 Exp 6 Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6
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  • 6. Expression Vectors As Points in ‘Expression Space’ Experiment 1 Experiment 2 Experiment 3 Similar Expression -0.8 -0.6 0.9 1.2 -0.3 1.3 -0.7 Exp 1 Exp 2 Exp 3 G1 G2 G3 G4 G5 -0.4 -0.4 -0.8 -0.8 -0.7 1.3 0.9 -0.6
  • 7. Distance and Similarity -the ability to calculate a distance (or similarity, it’s inverse) between two expression vectors is fundamental to clustering algorithms -distance between vectors is the basis upon which decisions are made when grouping similar patterns of expression -selection of a distance metric defines the concept of distance
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  • 9. Distance is Defined by a Metric 4.2 1.4 -1.00 -0.90 Euclidean Pearson(r*-1) Distance Metric : D D
  • 10. Normal distribution X = μ (mean of the distribution) σ = std. deviation of the distribution
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