Functional Analysis Talk - Revision history

Rf at 22:34, 11 May 2017

2017-05-11T22:34:32Z

Rf at 22:32, 11 May 2017

2017-05-11T22:32:59Z

Rf: Created page with "= Why do functional analysis? = * Statistical significance is not the same as biological significance * Variety of methods available to compare functional annotation to gene..."

2017-05-11T22:28:49Z

Created page with "= Why do functional analysis? = * Statistical significance is not the same as biological significance * Variety of methods available to compare functional annotation to gene..."

New page

= Why do functional analysis? =

* Statistical significance is not the same as biological significance
* Variety of methods available to compare functional annotation to gene data
* General aim is to identify gene functions/categories that show an interesting expression profile
* Potentially identify genes with smaller but biologically significant changes.

= Functional analysis methods =

* Positional Gene Enrichment – looks for regions of chromosome showing changed expression.
* The Ingenuity Pathways Analysis (IPA)
* Several methods use Gene Ontology (GO) terms or other "gene sets"
* GO is the means by which we identify function.
* Gene Set Enrichment Analysis (GSEA)
* GOAL: Gene Ontology AnaLyzer
* GOrilla

= Functional analysis methods =
[[File:fourcol.png]]

= Gene Set Enrichment Analysis =
[[File:rankintro.png]]

= Gene Set Enrichment Analysis =
[[File:line1.png]]

= Gene Set Enrichment Analysis =
[[File:line2.png]]

= Gene Set Enrichment Analysis =
[[File:line3.png]]

= Gene Set Enrichment Analysis =
[[File:highen.png]]

= Gene Set Enrichment Analysis =
[[File:eachgs.png]]

= Gene Set Enrichment Analysis =
[[File:nulldist.png]]

= Gene Set Enrichment Analysis =
[[File::gseawind.png]]
Example GSEA report of a gene set found to be enriched among down regulated genes in cancer samples

= Conclusions =
* A wide variety of methods are available for functional analysis of expression data
* Aids biological interpretation of the data
* Different types of annotation can be compared to expression data.
* Many methods do not require user specified thresholds

= Further reading =
* Eden et al "GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene" BMC Bioinformatics 2009
* Volinia et al "GOAL: a software tool for assessing biological significance of genes groups" Nucleic Acids Res 2004
* Tamayo, et al."Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles" PNAS 2005
* Preter et al "Positional gene enrichment analysis of gene sets for high-resolution of overrepresented chromosomal regions" Nucleic Acid Research 2008
* http://www.ingenuity.com/products/ipa

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 [[File:eachgs.png]]
-= Gene Set Enrichment Analysis =
+= Further shufflings =
 [[File:nulldist.png]]
 = Gene Set Enrichment Analysis =
-[[File::gseawind.png]]
+[[File:gseawind.png]]
-Example GSEA report of a gene set found to be enriched among down regulated genes in cancer samples
+* Example GSEA report of a gene set found to be enriched among down regulated genes in cancer samples
 = Conclusions =

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 * GOrilla
-= Functional analysis methods =
+= A functional analysis method =
 [[File:fourcol.png]]
-= Gene Set Enrichment Analysis =
+= First order by measure of DE =
 [[File:rankintro.png]]
-= Gene Set Enrichment Analysis =
+= Compare to list =
 [[File:line1.png]]
-= Gene Set Enrichment Analysis =
+= Move through each gene 1 =
 [[File:line2.png]]
-= Gene Set Enrichment Analysis =
+= Move through each gene 2 =
 [[File:line3.png]]
-= Gene Set Enrichment Analysis =
+= Highest Level identified =
 [[File:highen.png]]
-= Gene Set Enrichment Analysis =
+= Repetition of Process =
 [[File:eachgs.png]]