#acl All:read DanieleMerico:write,delete,revert
== 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 ==
== 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 ==
* Functional 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/21085640