#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 ==
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.

== 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).
== Network Propagation Algorithms ==
 * '''cancer mutations'''
   * Vandin F, Upfal E, Raphael BJ<<BR>>
   Algorithms for Detecting Significantly Mutated Pathways in Cancer<<BR>>
   LECTURE NOTES IN BIOINFORMATICS 2010, Volume: 6044, Pages: 506-521<<BR>>   
   [[http://www.springerlink.com/content/u7k4802m2np6/#section=696907&page=1&locus=0|PDF]]
 * '''signaling'''
   * Stojmirović A, Yu YK.<<BR>>
   Information flow in interaction networks.<<BR>>
   J Comput Biol. 2007 Oct;14(8):1115-43.<<BR>>
   http://www.ncbi.nlm.nih.gov/pubmed/17985991
   * Stojmirović A, Yu YK.<<BR>>
   ITM Probe: analyzing information flow in protein networks.<<BR>>
   Bioinformatics. 2009 Sep 15;25(18):2447-9. Epub 2009 Jun 27.<<BR>>
   http://www.ncbi.nlm.nih.gov/pubmed/19561335

== Other paper to look at ==
 * 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
 * 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
 * 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
Better publication probably coming soon:
 * MAGENTA <<BR>>
 Ayellet V. Segrè, DIAGRAM Consortium, MAGIC investigators, Leif Groop, Vamsi K. Mootha, Mark J. Daly, and David Altshuler (2010). <<BR>>
 Common Inherited Variation in Mitochondrial Genes is not Enriched for Associations with Type 2 Diabetes or Related Glycemic Traits. <<BR>>
 PLoS Genetics Aug 12;6(8). pii: e1001058. <<BR>>