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

• 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/20360734

• Bioinformatics 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.abstract

• 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

• Pathway-based analysis using reduced gene subsets in genome-wide association studies
  http://www.biomedcentral.com/1471-2105/12/17/abstract

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