//localhost:4321/key-objective-2/agatashakira-the-aop-project-part-10/index.html The AOP project ► Key objective 2 Author: Shakira Agata This Jupyter Notebook shows the steps for the execution of KE enrichment analysis and benchmarking to Overrepresentation Analysis(ORA) for dataset: GSE44729 This notebook is subdivided into nine sections: Section 1: Creation of dictKE dictionary Section 2: Creation of dictWP dictionary Section 3: Creation of KEgenes dictionary Section 4: Calculation of N variable Section 5: Comparison 1: Acrolein timepoint 2 Section 5.1: Calculation of n variable Section 5.2:Calculation of variable B and variable b Section 5.3: Calculation of enrichment score & hypergeometric p-value Section 5.4: Filtering results Section 5.5: Calculation of percent gene overlap Section 5.5.1 Creation of significant KE table Section 5.5.2 Significant ORA pathway table Section 5.5.3 Creation of for loop Section 5.5.4 Tabulation Section 5.5.5 Percent overlap calculation Section 6: Comparison 2: Chloropicrin timepoint 1 Section 6.1: Calculation of n variable Section 6.2:Calculation of variable B and variable b Section 6.3: Calculation of enrichment score & hypergeometric p-value Section 6.4: Filtering results Section 6.5: Calculation of percent gene overlap Section 6.5.1 Creation of significant KE table Section 6.5.2 Significant ORA pathway table Section 6.5.3 Creation of for loop Section 6.5.4 Tabulation Section 6.5.5 Percent overlap calculation Section 7: Comparison 3: Chloropicrin timepoint 2 Section 7.1: Calculation of n variable Section 7.2:Calculation of variable B and variable b Section 7.3: Calculation of enrichment score & hypergeometric p-value Section 7.4: Filtering results Section 7.5: Calculation of percent gene overlap Section 7.5.1 Creation of significant KE table Section 7.5.2 Significant ORA pathway table Section 7.5.3 Creation of for loop Section 7.5.4 Tabulation Section 7.5.5 Percent overlap calculation Section 8: Comparison 4: Maleic anhydride timepoint 2 Section 8.1: Calculation of n variable Section 8.2:Calculation of variable B and variable b Section 8.3: Calculation of enrichment score & hypergeometric p-value Section 8.4: Filtering results Section 8.5: Calculation of percent gene overlap Section 8.5.1 Creation of significant KE table Section 8.5.2 Significant ORA pathway table Section 8.5.3 Creation of for loop Section 8.5.4 Tabulation Section 8.5.5 Percent overlap calculation Section 9: Metadata Section 1: Creation of dictKE dictionary In this section, the dictKE dictionary will be made which is used to retrieve the first neighbors of the key events present in the inflammatory stress response pathway AOP network. Hugo en