Serial Expression Analysis
Serial Expression Analysis (SEA) is a web site for the analysis of serial gene expression data. Serial data is understood as multifactorial experimental designs where one of the factors is a quantitative variable such as time or treatment dose. The site offers five different methodologies for the identification of genes and functional classes which significant changes across series.
The following table summarizes the main characteristics of the SEA algorithms:
| Name | Statistical Strategy | Selected Features | Selection criterion |
| maSigPro | Univariate Regression | Genes | Genes with differential expression profiles |
| maSigFun | Univariate Regression | Functional Categories | Functional classes with most genes having correlated differential expression profiles |
| ASCA-genes | ANOVA + Multivariate Projection | Genes | Genes that follow major expression trends |
| ASCA-functional | ANOVA + Multivariate Projection + GSA | Functional Categories | Functional classes associated to a given expression trend |
| PCA-maSigFun | Multivariate Projection + Univariate Regression | Functional Categories | Functional classes with subset of genes showing correlated differential expression profiles |
