Functional enrichment analysis

Transcription

1 Functional enrichment analysis

2 Enrichment analysis Does my gene list (eg. up-regulated genes between two condictions) contain more genes than expected involved in a particular pathway or biological process (eg. cell cycle)? Hypergeometric test Fisher exact test Bionomial test (Bernouilli) Chi sq test

3 Enrichment analysis - For lists of genes C A B in list with annotation D tested

4 Contingency table Observed in list not in list totals with annotation A B A+B without annotation C D C+D A+C B+D A+B+C+D=N Expected in list not in list totals with annotation (A+B)(A+C)/N (A+B)(B+D)/N A+B without annotation (C+D)(A+C)/N (C+D)(B+D)/N C+D A+C B+D N

5 Enrichment analysis - For lists of genes in list with annotation 130 tested (183)

6 Contingency table - example Observed in list not in list totals with annotation A+B without annotation C+D A+C B+D A+B+C+D=N Expected in list not in list totals with annotation (A+B)(A+C)/N (A+B)(B+D)/N A+B without annotation (C+D)(A+C)/N (C+D)(B+D)/N C+D A+C B+D N

7 O = Observed / E = Expected Contingency table - example - Chi square test Observed in list not in list totals with annotation without annotation Expected in list not in list totals with annotation without annotation

8 Contingency table - example - Fisher s exact test Observed in list not in list totals with annotation without annotation Expected in list not in list totals with annotation without annotation

9 Enrichment analysis - For continuous values Are the values (eg. expression values) of the genes involved in a particular pathway or biological process (eg. cell cycle) biased towards high or low values? Blue ticks = genes with an annotation

10 Enrichment analysis - Gene Set Enrichment Analysis

11 Enrichment analysis - Zscore with permutations X Blue ticks = genes with an annotation (eg. 78 genes)

12 Annotation sources (modules) Gene Ontology biological process, molecular function, cellular component Terms may have >1 parent (more general term) GO Slim: includes only general categories KEGG; REACTOME pathways Genes sharing a motif of regulated by the same protein/mirna (experimental or predicted) Genes found on the same chromosome Broad s Molecular Signatures Database (MSigDB) [any grouping that is biologically sensible]

13 Gene Ontology

14 KEGG pathways

15 Multiple Test Problem! Enrichment analysis on multiple annotations (eg. all Gene Ontology Terms / all KEGG pathways) involves multiple statistical tests Need to do multiple test correction

16 Functional Enrichment tools Method URL Platform Type EA type g:profiler WT DAVID WT EAL (modified Fisher s exact - EASE) Babelomics WT EAL, EAC (Fisher s exact) GOMINER WT EAL (Fisher s exact) ConceptGene WT EAL (modified Fisher s exact - EASE) Ingenuity WT - GSEA DS, CL, RP EAC (Kolmogorov Smirnov rank statistics) Gitools DS, CL EAL (Binomial distribution, Fisher s exact), EAC (z-test) BiNGO CP EAL (Hypergeometric distribution) GOstats RP EAL (conditional hypergeometric test) ipage DS, CL, WT EAC (mutual information) ToppGene WT EAL (Hypergeometric distribution) Code for platform type: WT: Web tool DS: Downloadable software CL: Command line options RP: R package (Bioconductor) CP: Cytoscape plugin Code for EA type: EAL: Enrichment analysis for a list of genes EAC: Enrichment analysis for continuous values

17 Limitations of functional enrichment analysis Annotation databases are incomplete Annotation bias in databases: some genes are more studied and in consequence more annotated than others Terminology problem poses a challenge to data integration Some pieces of information may be imprecise or incorrect: some annotations in GO are inferred from electronic annotations without any expert human involvement (mainly annotations at very high level of the ontology).

18 Visualization and analysis of genomic data using Interactive Heatmaps

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