1. Gene Set Enrichment Analysis

2. GSEA: Key Features Ranks all genes on array based on their differential expression Identifies gene sets whose member genes are clustered either towards top or bottom of the ranked list (i.e. up- or down regulated) Enrichment score calculated for each category Permutation test to identify significantly enriched categories Extensive gene sets provided via MolSig DB – GO, chromosome location, KEGG pathways, transcription factor or microRNA target genes

3. GSEA Each gene category tested by traversing ranked list Enrichment score starts at 0, weighted increment when a member gene encountered, weighted decrement otherwise Enrichment score – point where most different from zero Most significantly up-regulated genes Unchanged genes Most significantly down-regulated genes Disease Control

4. Enrichment Score (ES) is calculated by evaluating the fractions of genes in S (‘‘hits’’) weighted by their correlation and the fractions of genes not in S (‘‘misses’’) present up to a given position i in the ranked gene list, L, where N genes are ordered according to the correlation, 4 Enrichment Score

5. GSEA algorithm

6. Null distribution of enrichment scores Actual ES GSEA: Permutation Test Randomise data (groups), rank genes again and repeat test 1000 times Null distribution of 1000 ES for geneset FDR q-value computed – corrected for gene set size and testing multiple gene sets