Literature and links mentioned in lecture 14

Literature and Links to sites mentioned in Lecture 14

Literature

Review of GO
Use and misuse of the gene ontology annotations
Rhee SY, Wood V, Dolinski K, Draghici S.
Nat Rev Genet. 2008 Jul;9(7):509-15.
Consistency of GO analysis over time
Monitoring changes in the Gene Ontology and their impact on genomic data analysis
Jacobson M, Sedeno-Cortes AS, Pavlidis P.
GigaScience. 2018 August;7(8)
Review of 68 gene enrichment tools
Bioinformatics enrichment tools: paths toward the comprehensive functional a nalysis of large gene lists
Huang da W, Sherman BT, Lempicki RA.
Nucleic Acids Res. 2009 Jan;37(1):1-13.
The Topology-weighted and Topolgy-elim algorithms
Improved scoring of functional groups from gene expression data by decorrela ting GO graph structure
Alexa A, Rahnenfuhrer J, Lengauer T.
Bioinformatics. 2006 Jul 1;22(13):1600-7.
The Parent-Child algorithms
Improved detection of overrepresentation of Gene-Ontology annotations with parent child analysis
Grossmann S, Bauer S, Robinson PN, Vingron M.
Bioinformatics. 2007 Nov 15;23(22):3024-31.
MGSA algorithm
GOing Bayesian: model-based gene set analysis of genome-scale data
Bauer S, Gagneur J, Robinson PN.
Nucleic Acids Research. 2010 Feb 19; 38(11):3523-3532.
Ontologizer paper
Ontologizer 2.0--a multifunctional tool for GO term enrichment analysis and data exploration
Bauer S, Grossmann S, Vingron M, Robinson PN.
Bioinformatics. 2008 Jul 15;24(14):1650-1.
DAVID paper (including step-by-step instructions)
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang da W, Sherman BT, Lempicki RA.
Nat Protoc. 2009;4(1):44-57.