Download TIGR MultipleExperimentViewer (MEV)

7.5.
Table Views....................................................................................................... 47
7.6.
Common Viewer Activities................................................................................ 49
8. Working with Clusters ......................................................... 51
8.1.
Storing Clusters and Using the Cluster Manager ............................................ 51
9. Utilities Menu ........................................................................ 58
10. Creating Output.................................................................... 63
10.1.
Saving the Analysis ....................................................................................... 63
10.2.
Saving the Expression Matrix ....................................................................... 63
10.3.
Saving Viewer Images................................................................................... 64
10.4.
Saving Cluster Data...................................................................................... 64
11. Modules.................................................................................. 65
Description Conventions and General Pointers ........................................................... 65
11.1.
HCL: Hierarchical clustering....................................................................... 67
11.2.
TEASE: Tree-EASE....................................................................................... 72
11.3.
ST: Support Trees ......................................................................................... 78
11.4.
SOTA: Self Organizing Tree Algorithm........................................................ 81
11.5.
RN: Relevance Networks............................................................................... 86
11.6.
KMC: K-Means/K-Medians Clustering ........................................................ 89
11.7.
KMS: K-Means / K-Medians Support ........................................................... 91
11.8.
CAST: Clustering Affinity Search Technique ............................................... 93
11.9.
QTC: QT CLUST .......................................................................................... 95
11.10.
SOM: Self Organizing Maps......................................................................... 97
11.11.
GSH: Gene Shaving .................................................................................... 100
11.12.
FOM: Figures of Merit ............................................................................... 102
11.13.
PTM: Template Matching ........................................................................... 106
11.14.
TTEST: T-tests ............................................................................................ 109
11.15.
SAM: Significance Analysis of Microarrays............................................... 117
11.16.
ANOVA: Analysis of Variance .................................................................... 121
11.17.
TFA: Two-factor ANOVA ........................................................................... 124
11.18.
SVM: Support Vector Machines.................................................................. 126
11.19.
KNNC: K-Nearest-Neighbor Classification ............................................... 133
11.20.
DAM: Discriminant Analysis Module......................................................... 137
11.21.
LEM: Linear Expression Maps................................................................... 142
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