Table 1 Statistical algorithms used in analysis of microarray data
Statistical algorithms | Characteristics | References | Sources |
|---|---|---|---|
Significance analysis of microarrays (SAM) | Identifies differentially expressed genes between sample sets; estimates significance for genes; considers large numbers of genes in array experiments | [9] | Stanford University, http://www-stat.stanford.edu/~tibs/ x-mine, Brisbane, CA, http://www.x-mine.com/ |
Hierarchal clustering | Unsupervised clustering; clusters genes with similar expression patterns; clusters samples with similar expression patterns | [15] | University of California, Berkeley, http://rana.lbl.gov/EisenSoftware.htm |
Supervised harvesting classification | Class prediction; identifies subset of genes that best classify samples as gene sets; estimates accuracy of gene set on prospective population | [10] | x-mine, Brisbane, CA, http://www.x-mine.com/ |
Classification and regression trees (CART), multiple additive regression trees (MART) | Class prediction; develops decision trees to classify samples using the expression of a subset of genes; estimates accuracy of the gene panel on a prospective set | CART: Salford Systems, http://www.salford-systems.com/ MART: Stanford University, http://www-stat.stanford.edu/~jhf/R-MART.html or Salford Systems | |
Shrunken centroids (prediction analysis for microarrays, PAM) | Class prediction; identifies subset of genes that best classify samples as gene sets; estimates accuracy of gene set on prospective population | [11] | Stanford University, http://www-stat.stanford.edu/~tibs/PAM/index.html |
Affymetrix MAS 5.0 | Affymetrix | ||
GeneSpring | Silicon Genetics | ||
Pathways 3.0 | Research Genetics |