Testing in microbiome-profiling studies with MiRKAT, the microbiome regression-based kernel association test

American Journal of Human Genetics

Volumn 96, Issue 5, 2015, Pages 797-807

  Zhao, Ni ^a   Chen, Jun ^b   Carroll, Ian M ^c   Ringel Kulka, Tamar ^d   Epstein, Michael P ^e   Zhou, Hua ^f   Zhou, Jin J ^g   Ringel, Yehuda ^c   Li, Hongzhe ^h   Wu, Michael C ^a  

^a Fred Hutchinson Cancer Research Center   (United States)

^b MAYO CLINIC   (United States)

^c UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^d IL   (United States)

^e EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^f NORTH CAROLINA STATE UNIVERSITY   (United States)

^g UNIVERSITY OF ARIZONA   (United States)

^h UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CALCULATION; CONTROLLED STUDY; COVARIANCE; GENETIC ASSOCIATION; GENETIC DISTANCE; HIGH THROUGHPUT SEQUENCING; KERNEL METHOD; MICROBIAL COMMUNITY; MICROBIAL DIVERSITY; MICROBIOME; MICROBIOME REGRESSION BASED KERNEL ASSOCIATION TEST; MOLECULAR PHYLOGENY; NONHUMAN; NONPARAMETRIC TEST; OUTCOME VARIABLE; PRIORITY JOURNAL; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL SIGNIFICANCE; SURVIVAL; VARIANCE; COMPUTER PROGRAM; COMPUTER SIMULATION; GENETICS; HUMAN; MICROFLORA; PHYLOGENY; POPULATION GENETICS; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL;

COMPUTER SIMULATION; GENETICS, POPULATION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MICROBIOTA; MODELS, STATISTICAL; PHYLOGENY; POLYMORPHISM, SINGLE NUCLEOTIDE; SOFTWARE;

EID: 84929159912     PISSN: 00029297     EISSN: 15376605     Source Type: Journal    
DOI: 10.1016/j.ajhg.2015.04.003     Document Type: Article

References (39)

1. C.R. Woese, G.E. Fox, L. Zablen, T. Uchida, L. Bonen, K. Pechman, B.J. Lewis, and D. Stahl Conservation of primary structure in 16S ribosomal RNA Nature 254 1975 83 86
2. G.W. Tyson, J. Chapman, P. Hugenholtz, E.E. Allen, R.J. Ram, P.M. Richardson, V.V. Solovyev, E.M. Rubin, D.S. Rokhsar, and J.F. Banfield Community structure and metabolism through reconstruction of microbial genomes from the environment Nature 428 2004 37 43
3. J.C. Wooley, A. Godzik, and I. Friedberg A primer on metagenomics PLoS Comput. Biol. 6 2010 e1000667
4. R.S. Lasken Genomic sequencing of uncultured microorganisms from single cells Nat. Rev. Microbiol. 10 2012 631 640
5. B.P. Willing, S.L. Russell, and B.B. Finlay Shifting the balance: antibiotic effects on host-microbiota mutualism Nat. Rev. Microbiol. 9 2011 233 243
6. P.J. Turnbaugh, M. Hamady, T. Yatsunenko, B.L. Cantarel, A. Duncan, R.E. Ley, M.L. Sogin, W.J. Jones, B.A. Roe, and J.P. Affourtit A core gut microbiome in obese and lean twins Nature 457 2009 480 484
7. N. Larsen, F.K. Vogensen, F.W. van den Berg, D.S. Nielsen, A.S. Andreasen, B.K. Pedersen, W.A. Al-Soud, S.J. Sørensen, L.H. Hansen, and M. Jakobsen Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults PLoS ONE 5 2010 e9085
8. D.A. Peterson, D.N. Frank, N.R. Pace, and J.I. Gordon Metagenomic approaches for defining the pathogenesis of inflammatory bowel diseases Cell Host Microbe 3 2008 417 427
9. F.H. Karlsson, V. Tremaroli, I. Nookaew, G. Bergström, C.J. Behre, B. Fagerberg, J. Nielsen, and F. Bäckhed Gut metagenome in European women with normal, impaired and diabetic glucose control Nature 498 2013 99 103
10. B. McArdle, and M. Anderson Fitting multivariate models to community data: a comment on distance-based redundancy analysis Ecology 82 2001 290 297
11. M. Arumugam, J. Raes, E. Pelletier, D. Le Paslier, T. Yamada, D.R. Mende, G.R. Fernandes, J. Tap, T. Bruls, J.M. Batto MetaHIT Consortium Enterotypes of the human gut microbiome Nature 473 2011 174 180
12. C. Lozupone, and R. Knight UniFrac: a new phylogenetic method for comparing microbial communities Appl. Environ. Microbiol. 71 2005 8228 8235
13. C.A. Lozupone, M. Hamady, S.T. Kelley, and R. Knight Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities Appl. Environ. Microbiol. 73 2007 1576 1585
14. J. Chen, K. Bittinger, E.S. Charlson, C. Hoffmann, J. Lewis, G.D. Wu, R.G. Collman, F.D. Bushman, and H. Li Associating microbiome composition with environmental covariates using generalized UniFrac distances Bioinformatics 28 2012 2106 2113
15. J. Chen, and H. Li Kernel Methods for Regression Analysis of Microbiome Compositional Data M. Hu, Y. Liu, J. Lin, Topics in Applied Statistics: 2012 Symposium of the International Chinese Statistical Association 2013 Springer 191 201
16. L.C. Kwee, D. Liu, X. Lin, D. Ghosh, and M.P. Epstein A powerful and flexible multilocus association test for quantitative traits Am. J. Hum. Genet. 82 2008 386 397
17. M.C. Wu, P. Kraft, M.P. Epstein, D.M. Taylor, S.J. Chanock, D.J. Hunter, and X. Lin Powerful SNP-set analysis for case-control genome-wide association studies Am. J. Hum. Genet. 86 2010 929 942
18. M.C. Wu, S. Lee, T. Cai, Y. Li, M. Boehnke, and X. Lin Rare-variant association testing for sequencing data with the sequence kernel association test Am. J. Hum. Genet. 89 2011 82 93
19. S. Lee, M.J. Emond, M.J. Bamshad, K.C. Barnes, M.J. Rieder, D.A. Nickerson, D.C. Christiani, M.M. Wurfel, X. Lin NHLBI GO Exome Sequencing Project - ESP Lung Project Team Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies Am. J. Hum. Genet. 91 2012 224 237
20. M.C. Wu, A. Maity, S. Lee, E.M. Simmons, Q.E. Harmon, X. Lin, S.M. Engel, J.J. Molldrem, and P.M. Armistead Kernel machine SNP-set testing under multiple candidate kernels Genet. Epidemiol. 37 2013 267 275
21. W. Chen, N. Zhao, M.C. Wu, D.J. Schaid, and J. Chen Small sample kernel association test for genetic association studies. Technical report 2015 Mayo Clinic
22. J.J. Goeman, S.A. van de Geer, F. de Kort, and H.C. van Houwelingen A global test for groups of genes: testing association with a clinical outcome Bioinformatics 20 2004 93 99
23. W. Pan Relationship between genomic distance-based regression and kernel machine regression for multi-marker association testing Genet. Epidemiol. 35 2011 211 216
24. D. Liu, X. Lin, and D. Ghosh Semiparametric regression of multidimensional genetic pathway data: least-squares kernel machines and linear mixed models Biometrics 63 2007 1079 1088
25. D. Liu, D. Ghosh, and X. Lin Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models BMC Bioinformatics 9 2008 292
26. D. Gianola, and J.B. van Kaam Reproducing kernel hilbert spaces regression methods for genomic assisted prediction of quantitative traits Genetics 178 2008 2289 2303
27. X. Lin Variance component testing in generalised linear models with random effects Biometrika 84 1997 309 326
28. H. Liu, Y. Tang, and H.H. Zhang A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables Comput. Stat. Data Anal. 53 2009 853 856
29. R. Davies The distribution of a linear combination of chi-2 random variables J. R. Stat. Soc. Ser. C Appl. Stat. 29 1980 323 333
30. P. Duchesne, and P. Lafaye de Micheaux Computing the distribution of quadratic forms: Further comparisons between the liu-tang-zhang approximation and exact methods Comput. Stat. Data Anal. 54 2010 858 862
31. D. Freedman, and D. Lane A nonstochastic interpretation of reported significance levels J. Bus. Econ. Stat. 1 1983 292 298
32. M.P. Epstein, R. Duncan, Y. Jiang, K.N. Conneely, A.S. Allen, and G.A. Satten A permutation procedure to correct for confounders in case-control studies, including tests of rare variation Am. J. Hum. Genet. 91 2012 215 223
33. A. Fog Sampling methods for wallenius' and fisher's noncentral hypergeometric distributions Commun. Stat. Simul. Comput. 37 2008 241 257
34. E.S. Charlson, J. Chen, R. Custers-Allen, K. Bittinger, H. Li, R. Sinha, J. Hwang, F.D. Bushman, and R.G. Collman Disordered microbial communities in the upper respiratory tract of cigarette smokers PLoS ONE 5 2010 e15216
35. A. Annaházi, K. Gecse, M. Dabek, A. Ait-Belgnaoui, A. Rosztóczy, R. Róka, T. Molnár, V. Theodorou, T. Wittmann, L. Bueno, and H. Eutamene Fecal proteases from diarrheic-IBS and ulcerative colitis patients exert opposite effect on visceral sensitivity in mice Pain 144 2009 209 217
36. I.M. Carroll, T. Ringel-Kulka, L. Ferrier, M.C. Wu, J.P. Siddle, L. Bueno, and Y. Ringel Fecal protease activity is associated with compositional alterations in the intestinal microbiota PLoS ONE 8 2013 e78017
37. C.M. Crainiceanu, and D. Ruppert Likelihood ratio tests in linear mixed models with one variance component J. R. Stat. Soc. Series B Stat. Methodol. 66 2004 165 185
38. S. Greven, C.M. Crainiceanu, H. Kchenhoff, and A. Peters Restricted likelihood ratio testing for zero variance components in linear mixed models J. Comput. Graph. Stat. 17 2008 870 891
39. G.I. Allen Automatic feature selection via weighted kernels and regularization J. Comput. Graph. Stat. 22 2013 284 299