Literature DB >> 22025762

The GA and the GWAS: using genetic algorithms to search for multilocus associations.

Michael Mooney1, Beth Wilmot, The Bipolar Genome Study, Shannon McWeeney.   

Abstract

Enormous data collection efforts and improvements in technology have made large genome-wide association studies a promising approach for better understanding the genetics of common diseases. Still, the knowledge gained from these studies may be extended even further by testing the hypothesis that genetic susceptibility is due to the combined effect of multiple variants or interactions between variants. Here we explore and evaluate the use of a genetic algorithm to discover groups of SNPs (of size 2, 3, or 4) that are jointly associated with bipolar disorder. The algorithm is guided by the structure of a gene interaction network, and is able to find groups of SNPs that are strongly associated with the disease, while performing far fewer statistical tests than other methods.

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Year:  2011        PMID: 22025762      PMCID: PMC3748153          DOI: 10.1109/TCBB.2011.145

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  22 in total

1.  Merlin--rapid analysis of dense genetic maps using sparse gene flow trees.

Authors:  Gonçalo R Abecasis; Stacey S Cherny; William O Cookson; Lon R Cardon
Journal:  Nat Genet       Date:  2001-12-03       Impact factor: 38.330

Review 2.  Mathematical multi-locus approaches to localizing complex human trait genes.

Authors:  Josephine Hoh; Jurg Ott
Journal:  Nat Rev Genet       Date:  2003-09       Impact factor: 53.242

3.  Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data.

Authors:  Benilton Carvalho; Henrik Bengtsson; Terence P Speed; Rafael A Irizarry
Journal:  Biostatistics       Date:  2006-12-22       Impact factor: 5.899

Review 4.  Detection of gene x gene interactions in genome-wide association studies of human population data.

Authors:  Solomon K Musani; Daniel Shriner; Nianjun Liu; Rui Feng; Christopher S Coffey; Nengjun Yi; Hemant K Tiwari; David B Allison
Journal:  Hum Hered       Date:  2007-02-02       Impact factor: 0.444

5.  PLINK: a tool set for whole-genome association and population-based linkage analyses.

Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
Journal:  Am J Hum Genet       Date:  2007-07-25       Impact factor: 11.025

6.  An APL-programmed genetic algorithm for the prediction of RNA secondary structure.

Authors:  F H van Batenburg; A P Gultyaev; C W Pleij
Journal:  J Theor Biol       Date:  1995-06-07       Impact factor: 2.691

7.  The future of genetic studies of complex human diseases.

Authors:  N Risch; K Merikangas
Journal:  Science       Date:  1996-09-13       Impact factor: 47.728

8.  Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results.

Authors:  E Lander; L Kruglyak
Journal:  Nat Genet       Date:  1995-11       Impact factor: 38.330

9.  Genetic algorithms: principles of natural selection applied to computation.

Authors:  S Forrest
Journal:  Science       Date:  1993-08-13       Impact factor: 47.728

10.  Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target.

Authors:  S Horvath; B Zhang; M Carlson; K V Lu; S Zhu; R M Felciano; M F Laurance; W Zhao; S Qi; Z Chen; Y Lee; A C Scheck; L M Liau; H Wu; D H Geschwind; P G Febbo; H I Kornblum; T F Cloughesy; S F Nelson; P S Mischel
Journal:  Proc Natl Acad Sci U S A       Date:  2006-11-07       Impact factor: 11.205

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  5 in total

1.  Improving predictive models for Alzheimer's disease using GWAS data by incorporating misclassified samples modeling.

Authors:  Brissa-Lizbeth Romero-Rosales; Jose-Gerardo Tamez-Pena; Humberto Nicolini; Maria-Guadalupe Moreno-Treviño; Victor Trevino
Journal:  PLoS One       Date:  2020-04-23       Impact factor: 3.240

Review 2.  Ant colony optimisation of decision tree and contingency table models for the discovery of gene-gene interactions.

Authors:  Emmanuel Sapin; Ed Keedwell; Tim Frayling
Journal:  IET Syst Biol       Date:  2015-12       Impact factor: 1.615

3.  Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives.

Authors:  Sebastian Okser; Tapio Pahikkala; Tero Aittokallio
Journal:  BioData Min       Date:  2013-03-01       Impact factor: 2.522

4.  Development and Application of a Genetic Algorithm for Variable Optimization and Predictive Modeling of Five-Year Mortality Using Questionnaire Data.

Authors:  Lucas J Adams; Ghalib Bello; Gerard G Dumancas
Journal:  Bioinform Biol Insights       Date:  2015-11-08

5.  A prostate cancer model build by a novel SVM-ID3 hybrid feature selection method using both genotyping and phenotype data from dbGaP.

Authors:  Sait Can Yücebaş; Yeşim Aydın Son
Journal:  PLoS One       Date:  2014-03-20       Impact factor: 3.240

  5 in total

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