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Other papers * Why olfactory receptors as false positives<<BR>> PLoS Genet. 2008 Nov;4(11):e1000249. Epub 2008 Nov 7.<<BR>> High-resolution copy-number variation map reflects human olfactory receptor diversity and evolution.<<BR>> Hasin Y, Olender T, Khen M, Gonzaga-Jauregui C, Kim PM, Urban AE, Snyder M, Gerstein MB, Lancet D, Korbel JO. |
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* Interesting large data-set<<BR>> Nature. 2010 Apr 1;464(7289):713-20.<<BR>> Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls.<<BR>> Wellcome Trust Case Control Consortium,<<BR>> http://www.ncbi.nlm.nih.gov/pubmed/20360734 |
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* Pathway-based analysis using reduced gene subsets in genome-wide association studies <<BR>> http://www.biomedcentral.com/1471-2105/12/17/abstract == Gene-set Tests for GWAS == Not in the Mendeley collection: * Pathways of Distinction Analysis: a new technique for multi-SNP analysis of GWAS data<<BR>> http://arxiv.org/abs/1012.4726 |
Association Analysis for Rare Variants
Statistical analysis strategies for association studies involving rare variants.
Bansal V, Libiger O, Torkamani A, Schork NJ.
Nat Rev Genet. 2010 Nov;11(11):773-85. Epub 2010 Oct 13. Review.
PMID: 20940738 http://www.ncbi.nlm.nih.gov/sites/entrez/20940738- focused on single nucleotide rare variants
links to > 10 association tests at the gene or genomic area level, with correction or subpopulation and covariates
- quite of an effort to understand and follow up on all the methods referenced
- briefly mentions pathway analysis (ref to Autism Nature paper)
An evaluation of statistical approaches to rare variant analysis in genetic association studies.
Morris AP, Zeggini E.
Genet Epidemiol. 2010 Feb;34(2):188-93.
PMID: 19810025
Gene-set Association Tests for Rare Variants
Other papers
Why olfactory receptors as false positives
PLoS Genet. 2008 Nov;4(11):e1000249. Epub 2008 Nov 7.
High-resolution copy-number variation map reflects human olfactory receptor diversity and evolution.
Hasin Y, Olender T, Khen M, Gonzaga-Jauregui C, Kim PM, Urban AE, Snyder M, Gerstein MB, Lancet D, Korbel JO.
Similar Gene-set Analysis Strategies for Genetics Data
Cancer Mutations
Patient-oriented gene set analysis for cancer mutation data
Boca SM, Kinzler K, Velculescu VE, Vogelstein B, Parmigiani G.
Genome Biol. 2010 Nov 23;11(11):R112.
PMID: 21092299 http://www.ncbi.nlm.nih.gov/sites/entrez/21092299- It's basically the same idea applied to cancer instead of autism.
- However, lacking the control patients (since cancer is high mutation frequency, that would not make sense), they have to define the null hypothesis using randomly placed mutations.
- What they call "exclusivity principle" is what I usually call the "OR combination logic" (i.e. at least one perturbed gene for the pathway/gene-set to be perturbed).
Other paper to look at
Interesting large data-set
Nature. 2010 Apr 1;464(7289):713-20.
Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls.
Wellcome Trust Case Control Consortium,
http://www.ncbi.nlm.nih.gov/pubmed/20360734Bioinformatics challenges for genome-wide association studies.
Moore JH, Asselbergs FW, Williams SM.
Bioinformatics. 2010 Feb 15;26(4):445-55. Epub 2010 Jan 6.
http://bioinformatics.oxfordjournals.org/content/26/4/445.abstractFunctional genomics complements quantitative genetics in identifying disease-gene associations.
Guan Y, Ackert-Bicknell CL, Kell B, Troyanskaya OG, Hibbs MA.
PLoS Comput Biol. 2010 Nov 11;6(11):e1000991
http://www.ncbi.nlm.nih.gov/pubmed/21085640Pathway-based analysis using reduced gene subsets in genome-wide association studies
http://www.biomedcentral.com/1471-2105/12/17/abstract
Gene-set Tests for GWAS
Not in the Mendeley collection:
Pathways of Distinction Analysis: a new technique for multi-SNP analysis of GWAS data
http://arxiv.org/abs/1012.4726