Perform Differential Expression Testing
For each gene, infers differential expression with respect to each specified covariate using a multivariate linear regression model with terms for all selected predictors and confounders. Results will only be displayed for covariates designated as predictors, but will have taken into account the effect of selected confounders. At least one covariate must be selected as a predictor for differential expression analysis to occur.
 
P-value adjustment
Outputs the Bonferroni adjusted p-value or Benjamini-Yekutieli False Discovery Rate (FDR).
 
Run Pathway Gene Significance Analysis (GSA)
Summarizes the statistical significance of all genes in a pathway using their mean squared t-statistic.
 
GSA will utilize the value of the Gene Sets Column selected on page 1.
        

Add Additional KEGG IDs for Analysis

Display Results Using Pathview
Uses Pathview (Luo et al., Bioinformatics, 2013) to overlay the results of the differential expression analyses on KEGG diagrams of the cancer panel pathways. Plots will be generated for the primary pathways that have KEGG maps available.
 
Only differential expression results exceeding the specified P-value threshold will be plotted.
 
Additional 5-digit KEGG IDs may entered. Omit the leading species prefix - eg hsa04012 (ErbB Signaling) would be entered as 04012.