Literature DB >> 26873927

An efficient gene-gene interaction test for genome-wide association studies in trio families.

Pei-Yuan Sung1, Yi-Ting Wang1, Ya-Wen Yu2, Ren-Hua Chung2.   

Abstract

MOTIVATION: Several efficient gene-gene interaction tests have been developed for unrelated case-control samples in genome-wide association studies (GWAS), making it possible to test tens of billions of interaction pairs of single-nucleotide polymorphisms (SNPs) in a reasonable timeframe. However, current family-based gene-gene interaction tests are computationally expensive and are not applicable to genome-wide interaction analysis.
RESULTS: We developed an efficient family-based gene-gene interaction test, GCORE, for trios (i.e. two parents and one affected sib). The GCORE compares interlocus correlations at two SNPs between the transmitted and non-transmitted alleles. We used simulation studies to compare the statistical properties such as type I error rates and power for the GCORE with several other family-based interaction tests under various scenarios. We applied the GCORE to a family-based GWAS for autism consisting of approximately 2000 trios. Testing a total of 22 471 383 013 interaction pairs in the GWAS can be finished in 36 h by the GCORE without large-scale computing resources, demonstrating that the test is practical for genome-wide gene-gene interaction analysis in trios.
AVAILABILITY AND IMPLEMENTATION: GCORE is implemented with C ++ and is available at http://gscore.sourceforge.net CONTACT: rchung@nhri.org.tw SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Mesh:

Year:  2016        PMID: 26873927      PMCID: PMC5939888          DOI: 10.1093/bioinformatics/btw077

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  39 in total

1.  Case/pseudocontrol analysis in genetic association studies: A unified framework for detection of genotype and haplotype associations, gene-gene and gene-environment interactions, and parent-of-origin effects.

Authors:  Heather J Cordell; Bryan J Barratt; David G Clayton
Journal:  Genet Epidemiol       Date:  2004-04       Impact factor: 2.135

2.  A linear complexity phasing method for thousands of genomes.

Authors:  Olivier Delaneau; Jonathan Marchini; Jean-François Zagury
Journal:  Nat Methods       Date:  2011-12-04       Impact factor: 28.547

3.  On the covariance of two correlated log-odds ratios.

Authors:  Pantelis G Bagos
Journal:  Stat Med       Date:  2012-02-03       Impact factor: 2.373

4.  A novel method to identify gene-gene effects in nuclear families: the MDR-PDT.

Authors:  E R Martin; M D Ritchie; L Hahn; S Kang; J H Moore
Journal:  Genet Epidemiol       Date:  2006-02       Impact factor: 2.135

5.  SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies.

Authors:  Can Yang; Zengyou He; Xiang Wan; Qiang Yang; Hong Xue; Weichuan Yu
Journal:  Bioinformatics       Date:  2008-12-19       Impact factor: 6.937

6.  Forward-time simulations of non-random mating populations using simuPOP.

Authors:  Bo Peng; Christopher I Amos
Journal:  Bioinformatics       Date:  2008-04-15       Impact factor: 6.937

7.  Testing gene-gene interactions in genome wide association studies.

Authors:  Jie Kate Hu; Xianlong Wang; Pei Wang
Journal:  Genet Epidemiol       Date:  2014-01-15       Impact factor: 2.135

8.  Autism genome-wide copy number variation reveals ubiquitin and neuronal genes.

Authors:  Joseph T Glessner; Kai Wang; Guiqing Cai; Olena Korvatska; Cecilia E Kim; Shawn Wood; Haitao Zhang; Annette Estes; Camille W Brune; Jonathan P Bradfield; Marcin Imielinski; Edward C Frackelton; Jennifer Reichert; Emily L Crawford; Jeffrey Munson; Patrick M A Sleiman; Rosetta Chiavacci; Kiran Annaiah; Kelly Thomas; Cuiping Hou; Wendy Glaberson; James Flory; Frederick Otieno; Maria Garris; Latha Soorya; Lambertus Klei; Joseph Piven; Kacie J Meyer; Evdokia Anagnostou; Takeshi Sakurai; Rachel M Game; Danielle S Rudd; Danielle Zurawiecki; Christopher J McDougle; Lea K Davis; Judith Miller; David J Posey; Shana Michaels; Alexander Kolevzon; Jeremy M Silverman; Raphael Bernier; Susan E Levy; Robert T Schultz; Geraldine Dawson; Thomas Owley; William M McMahon; Thomas H Wassink; John A Sweeney; John I Nurnberger; Hilary Coon; James S Sutcliffe; Nancy J Minshew; Struan F A Grant; Maja Bucan; Edwin H Cook; Joseph D Buxbaum; Bernie Devlin; Gerard D Schellenberg; Hakon Hakonarson
Journal:  Nature       Date:  2009-04-28       Impact factor: 49.962

9.  Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

Authors:  Peter Szatmari; Andrew D Paterson; Lonnie Zwaigenbaum; Wendy Roberts; Jessica Brian; Xiao-Qing Liu; John B Vincent; Jennifer L Skaug; Ann P Thompson; Lili Senman; Lars Feuk; Cheng Qian; Susan E Bryson; Marshall B Jones; Christian R Marshall; Stephen W Scherer; Veronica J Vieland; Christopher Bartlett; La Vonne Mangin; Rhinda Goedken; Alberto Segre; Margaret A Pericak-Vance; Michael L Cuccaro; John R Gilbert; Harry H Wright; Ruth K Abramson; Catalina Betancur; Thomas Bourgeron; Christopher Gillberg; Marion Leboyer; Joseph D Buxbaum; Kenneth L Davis; Eric Hollander; Jeremy M Silverman; Joachim Hallmayer; Linda Lotspeich; James S Sutcliffe; Jonathan L Haines; Susan E Folstein; Joseph Piven; Thomas H Wassink; Val Sheffield; Daniel H Geschwind; Maja Bucan; W Ted Brown; Rita M Cantor; John N Constantino; T Conrad Gilliam; Martha Herbert; Clara Lajonchere; David H Ledbetter; Christa Lese-Martin; Janet Miller; Stan Nelson; Carol A Samango-Sprouse; Sarah Spence; Matthew State; Rudolph E Tanzi; Hilary Coon; Geraldine Dawson; Bernie Devlin; Annette Estes; Pamela Flodman; Lambertus Klei; William M McMahon; Nancy Minshew; Jeff Munson; Elena Korvatska; Patricia M Rodier; Gerard D Schellenberg; Moyra Smith; M Anne Spence; Chris Stodgell; Ping Guo Tepper; Ellen M Wijsman; Chang-En Yu; Bernadette Rogé; Carine Mantoulan; Kerstin Wittemeyer; Annemarie Poustka; Bärbel Felder; Sabine M Klauck; Claudia Schuster; Fritz Poustka; Sven Bölte; Sabine Feineis-Matthews; Evelyn Herbrecht; Gabi Schmötzer; John Tsiantis; Katerina Papanikolaou; Elena Maestrini; Elena Bacchelli; Francesca Blasi; Simona Carone; Claudio Toma; Herman Van Engeland; Maretha de Jonge; Chantal Kemner; Frederieke Koop; Frederike Koop; Marjolein Langemeijer; Marjolijn Langemeijer; Channa Hijmans; Channa Hijimans; Wouter G Staal; Gillian Baird; Patrick F Bolton; Michael L Rutter; Emma Weisblatt; Jonathan Green; Catherine Aldred; Julie-Anne Wilkinson; Andrew Pickles; Ann Le Couteur; Tom Berney; Helen McConachie; Anthony J Bailey; Kostas Francis; Gemma Honeyman; Aislinn Hutchinson; Jeremy R Parr; Simon Wallace; Anthony P Monaco; Gabrielle Barnby; Kazuhiro Kobayashi; Janine A Lamb; Ines Sousa; Nuala Sykes; Edwin H Cook; Stephen J Guter; Bennett L Leventhal; Jeff Salt; Catherine Lord; Christina Corsello; Vanessa Hus; Daniel E Weeks; Fred Volkmar; Maïté Tauber; Eric Fombonne; Andy Shih; Kacie J Meyer
Journal:  Nat Genet       Date:  2007-02-18       Impact factor: 38.330

10.  A groupwise association test for rare mutations using a weighted sum statistic.

Authors:  Bo Eskerod Madsen; Sharon R Browning
Journal:  PLoS Genet       Date:  2009-02-13       Impact factor: 5.917

View more
  4 in total

1.  Identifying gene-gene interactions using penalized tensor regression.

Authors:  Mengyun Wu; Jian Huang; Shuangge Ma
Journal:  Stat Med       Date:  2017-10-16       Impact factor: 2.373

2.  SAMA: A Fast Self-Adaptive Memetic Algorithm for Detecting SNP-SNP Interactions Associated with Disease.

Authors:  Ying Yin; Boxin Guan; Yuhai Zhao; Yuan Li
Journal:  Biomed Res Int       Date:  2020-08-24       Impact factor: 3.411

3.  Self-Adjusting Ant Colony Optimization Based on Information Entropy for Detecting Epistatic Interactions.

Authors:  Boxin Guan; Yuhai Zhao
Journal:  Genes (Basel)       Date:  2019-02-01       Impact factor: 4.096

4.  HiSeeker: Detecting High-Order SNP Interactions Based on Pairwise SNP Combinations.

Authors:  Jie Liu; Guoxian Yu; Yuan Jiang; Jun Wang
Journal:  Genes (Basel)       Date:  2017-05-31       Impact factor: 4.096

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.