ExGeneOntology R - Revision history

Krivi: /* Enrichment analysis - reexamining cluster #1 */

2025-09-17T10:16:10Z

Enrichment analysis - reexamining cluster #1

← Older revision		Revision as of 12:16, 17 September 2025
Line 235:		Line 235:
	# The '''enrichment''' of observed GO terms compared to expected		# The '''enrichment''' of observed GO terms compared to expected
	# The p-value for each GO term (use <code>fisher.test()</code> in RStudio)		# The p-value for each GO term (use <code>fisher.test()</code> in RStudio)
	# What will happen to the P-value and odds ratio (calculated by <code>fisher.test()</code>) if the background was 500 genes,100,000 genes? What does this mean for the choice of background?		# What will happen to the P-value and odds ratio (calculated by <code>fisher.test()</code>) if the background was 500 genes,100,000 genes? Calculate the result and comment on it. What does this mean for the choice of background?

	<!--		<!--

Krivi: /* Enrichment analysis - reexamining cluster #1 */

2025-09-11T12:13:27Z

Enrichment analysis - reexamining cluster #1

← Older revision		Revision as of 14:13, 11 September 2025
Line 235:		Line 235:
	# The '''enrichment''' of observed GO terms compared to expected		# The '''enrichment''' of observed GO terms compared to expected
	# The p-value for each GO term (use <code>fisher.test()</code> in RStudio)		# The p-value for each GO term (use <code>fisher.test()</code> in RStudio)
	# What will happen to the P-value and odds ratio (calculated by <code>fisher.test()</code>) if the background was ~~1000~~ genes,100,000 genes?		# What will happen to the P-value and odds ratio (calculated by <code>fisher.test()</code>) if the background was 500 genes,100,000 genes? What does this mean for the choice of background?

	<!--		<!--

Krivi: /* Enrichment analysis - reexamining cluster #1 */

2025-09-11T11:52:07Z

Enrichment analysis - reexamining cluster #1

← Older revision		Revision as of 13:52, 11 September 2025
Line 235:		Line 235:
	# The '''enrichment''' of observed GO terms compared to expected		# The '''enrichment''' of observed GO terms compared to expected
	# The p-value for each GO term (use <code>fisher.test()</code> in RStudio)		# The p-value for each GO term (use <code>fisher.test()</code> in RStudio)
			# What will happen to the P-value and odds ratio (calculated by <code>fisher.test()</code>) if the background was 1000 genes,100,000 genes?

	<!--		<!--

Krivi: /* Enrichment analysis - reexamining cluster #1 */

2025-09-11T11:50:16Z

Enrichment analysis - reexamining cluster #1

← Older revision		Revision as of 13:50, 11 September 2025
Line 228:		Line 228:

	[[Image:Office-notes-line_drawing.png\|30px\|left]]		[[Image:Office-notes-line_drawing.png\|30px\|left]]
	'''TASK/REPORT QUESTION #7:''' Assuming a total of '''5500''' annotated genes calculate/report the following values:		'''TASK/REPORT QUESTION #7:''' Assuming a total of '''5500''' annotated genes (background for this exercise) calculate/report the following values:
	# Population group size		# Population group size
	# Study group size		# Study group size

Krivi: /* Part 2: Gene Ontology overrepresentation analysis (ORA) */

2025-09-11T11:49:13Z

Part 2: Gene Ontology overrepresentation analysis (ORA)

← Older revision		Revision as of 13:49, 11 September 2025
Line 151:		Line 151:
	* The subset (study group) could be a set of overexpressed genes from a RNAseq experiment, or simply a list of genes which you for other reasons expect to be involved in the same biological process.		* The subset (study group) could be a set of overexpressed genes from a RNAseq experiment, or simply a list of genes which you for other reasons expect to be involved in the same biological process.
	'''Population group:'''		'''Population group:'''
	* The population group would then be defined as the '''background''' to compare to - e.g. the entire list of genes, or in the case of gene expression all genes ~~represented on~~ the ~~microarray~~. We can then ask if the frequency of proteins annotation to a GO term is different for the study group compared to the overall population.		* The population group would then be defined as the '''background''' to compare to - e.g. the entire list of genes, or in the case of gene expression all genes that had the possiblity of ending in the final list (e.g. all genes tested for statistical significance). We can then ask if the frequency of proteins annotation to a GO term is different for the study group compared to the overall population.

	== Enrichment analysis - reexamining cluster #1 ==		== Enrichment analysis - reexamining cluster #1 ==

Krivi: /* Repeat analysis on selected clusters */

2025-09-10T08:36:36Z

Repeat analysis on selected clusters

← Older revision		Revision as of 10:36, 10 September 2025
Line 357:		Line 357:

	[[Image:Office-notes-line_drawing.png\|30px\|left]]		[[Image:Office-notes-line_drawing.png\|30px\|left]]
	'''TASK/REPORT QUESTION #12:''' perform the following over-representation analysis and create a short report documenting you finding:		'''TASK/REPORT QUESTION #10:''' perform the following over-representation analysis and create a short report documenting you finding:
	* Biological Process		* Biological Process
	* Molecular function		* Molecular function

Krivi: /* Preparing input data */

2025-09-10T08:36:27Z

Preparing input data

← Older revision		Revision as of 10:36, 10 September 2025
Line 333:		Line 333:
	Before we proceed, take a moment to explore the functions "fora" and "msigdbr". In particular, take a look at what object class the "fora" function expects the gene sets to be, and what object class is produced by "msigdbr" with the command above?		Before we proceed, take a moment to explore the functions "fora" and "msigdbr". In particular, take a look at what object class the "fora" function expects the gene sets to be, and what object class is produced by "msigdbr" with the command above?

	'''TASK/REPORT QUESTION #11:''' Can you directly use the gene sets produced by the msigdbr function as input for the "fora" function of "fgsea"? Why/why not?		'''TASK/REPORT QUESTION #8:''' Can you directly use the gene sets produced by the msigdbr function as input for the "fora" function of "fgsea"? Why/why not?

	<br>		<br>
Line 351:		Line 351:

	[[Image:Office-notes-line_drawing.png\|30px\|left]]		[[Image:Office-notes-line_drawing.png\|30px\|left]]
	'''TASK/REPORT QUESTION #12:''' Run the analysis for cluster #1 for all three GO trunks (Biological Process, Molecular Function and Cellular Component), and include top 10 significantly enriched GO terms for each ontology. Add a section to your report discussing if the results fit with what we have previously learned about the function of cluster #1.		'''TASK/REPORT QUESTION #9:''' Run the analysis for cluster #1 for all three GO trunks (Biological Process, Molecular Function and Cellular Component), and include top 10 significantly enriched GO terms for each ontology. Add a section to your report discussing if the results fit with what we have previously learned about the function of cluster #1.

	== Repeat analysis on selected clusters ==		== Repeat analysis on selected clusters ==

Krivi: /* Enrichment analysis - reexamining cluster #1 */

2025-09-10T08:35:52Z

Enrichment analysis - reexamining cluster #1

← Older revision		Revision as of 10:35, 10 September 2025
Line 228:		Line 228:

	[[Image:Office-notes-line_drawing.png\|30px\|left]]		[[Image:Office-notes-line_drawing.png\|30px\|left]]
	'''TASK/REPORT QUESTION #9:''' Assuming a total of '''5500''' annotated genes calculate/report the following values:		'''TASK/REPORT QUESTION #7:''' Assuming a total of '''5500''' annotated genes calculate/report the following values:
	# Population group size		# Population group size
	# Study group size		# Study group size
Line 284:		Line 284:

	[[Image:Office-notes-line_drawing.png\|30px\|left]]		[[Image:Office-notes-line_drawing.png\|30px\|left]]
	'''TASK/REPORT QUESTION #10:'''		'''TASK/REPORT QUESTION #8:'''
	* Calculate the p-values for the '''cluster #1''' example above.		* Calculate the p-values for the '''cluster #1''' example above.
	* ''Use the same assumptions as in question 12''.		* ''Use the same assumptions as in question 12''.

Krivi: /* UniProt */

2025-09-10T08:35:14Z

UniProt

← Older revision		Revision as of 10:35, 10 September 2025
Line 132:		Line 132:

	[[Image:Office-notes-line_drawing.png\|30px\|left]]		[[Image:Office-notes-line_drawing.png\|30px\|left]]
	'''TASK/REPORT QUESTION #8: look up human POLD1 in [http://www.uniprot.org UniProt]''':		'''TASK/REPORT QUESTION #6: look up human POLD1 in [http://www.uniprot.org UniProt]''':
	* Entry name: DPOD1_HUMAN or P28340.		* Entry name: DPOD1_HUMAN or P28340.
	* Locate the "Function" and "Subcellular Location" sections.		* Locate the "Function" and "Subcellular Location" sections.

Krivi: /* Repeat analysis on selected clusters */

2025-09-10T08:34:37Z

Repeat analysis on selected clusters

← Older revision		Revision as of 10:34, 10 September 2025
Line 354:		Line 354:

	== Repeat analysis on selected clusters ==		== Repeat analysis on selected clusters ==
	[[Image:Cogs_brain.png\|50px]] As the final task of today's exercise we'll be re-visiting the ~~'''10~~ clusters~~''' from last week's exercise~~. ~~Pick the '''3 clusters''' which appear the most interesting to you~~.		[[Image:Cogs_brain.png\|50px]] As the final task of today's exercise we'll be re-visiting the other clusters in the interaction data. Randomly pick another cluster.

	[[Image:Office-notes-line_drawing.png\|30px\|left]]		[[Image:Office-notes-line_drawing.png\|30px\|left]]
Line 363:		Line 363:
	* Question:		* Question:
	** Do the results make biological sense?		** Do the results make biological sense?
	** ~~How do these results compare to~~ the ~~broad categories we observed in the previous exercise~~?		What is the likely function of this cluster?