Background operations

ReactomeGSA offers three algorithms. PADOG and Camera perform a differential expression analysis between two groups of samples. ssGSEA is a so-called gene set variation approach that returns pathway-level quantitative data for each sample.

PADOG: Pathway Analysis with Down-weighting of Overlapping Genes (PADOG) computes a gene set score based on gene weights that are designed to emphasize the genes appearing in few gene sets, versus genes that appear in many gene sets (uniqueness of genes). 

Camera: Inter-gene correlations can skew analysis results and Correlation Adjusted MEan RAnk gene set test (Camera) is based on the idea of estimating the inter-gene correlation from the data, and using it to adjust the gene set test statistic. 

ssGSEA: Single-sample GSEA (ssGSEA) calculates separate enrichment scores for each pairing of a sample (input data) and gene set (pathway).  Each ssGSEA enrichment score represents the degree to which the genes in a particular gene set are coordinately up- or down-regulated within a sample.