#acl All:read DanieleMerico:write,delete,revert
== Association Analysis for Rare Variants ==
 * '''Statistical analysis strategies for association studies involving rare variants.'''<<BR>>
 Bansal V, Libiger O, Torkamani A, Schork NJ.<<BR>>
 Nat Rev Genet. 2010 Nov;11(11):773-85. Epub 2010 Oct 13. Review.<<BR>>
 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.'''<<BR>>
 Morris AP, Zeggini E.<<BR>>
 Genet Epidemiol. 2010 Feb;34(2):188-93.<<BR>>
 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'''<<BR>>
 Boca SM, Kinzler K, Velculescu VE, Vogelstein B, Parmigiani G.<<BR>>
 Genome Biol. 2010 Nov 23;11(11):R112.<<BR>>
 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 ==
 * Bioinformatics challenges for genome-wide association studies.<<BR>>
 Moore JH, Asselbergs FW, Williams SM.<<BR>>
 Bioinformatics. 2010 Feb 15;26(4):445-55. Epub 2010 Jan 6.<<BR>>
 http://bioinformatics.oxfordjournals.org/content/26/4/445.abstract
 * Functional genomics complements quantitative genetics in identifying disease-gene associations.<<BR>>
 Guan Y, Ackert-Bicknell CL, Kell B, Troyanskaya OG, Hibbs MA.<<BR>>
 PLoS Comput Biol. 2010 Nov 11;6(11):e1000991<<BR>>
 http://www.ncbi.nlm.nih.gov/pubmed/21085640