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Volumn , Issue , 2010, Pages

Sparse instrumental variables (SPIV) for genome-wide studies

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[No Author keywords available]

Indexed keywords

GENES;

EID: 85161983458     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (12)

References (42)
  • 1
    • 77952313673 scopus 로고    scopus 로고
    • Genome-wide association study of circulating vitamin D levels
    • Epub ahead of print
    • J. Ahn, K. Yu, and R. Stolzenberg-Solomon et. al. Genome-wide association study of circulating vitamin D levels. Human Molecular Genetics, 2010. Epub ahead of print.
    • (2010) Human Molecular Genetics
    • Ahn, J.1    Yu, K.2    Stolzenberg-Solomon, R.3
  • 2
    • 0346880128 scopus 로고    scopus 로고
    • Identification of causal effects using instrumental variables (with discussion)
    • J. D. Angrist, G.W. Imbens, and D. B. Rubin. Identification of causal effects using instrumental variables (with discussion). J. of the Am. Stat. Assoc., 91:444-455, 1996.
    • (1996) J. of the Am. Stat. Assoc. , vol.91 , pp. 444-455
    • Angrist, J.D.1    Imbens, G.W.2    Rubin, D.B.3
  • 4
    • 9444235509 scopus 로고    scopus 로고
    • Generalized instrumental variables
    • C. Brito and J. Pearl. Generalized instrumental variables. In UAI, 2002.
    • (2002) UAI
    • Brito, C.1    Pearl, J.2
  • 5
    • 40749105508 scopus 로고    scopus 로고
    • Variations in DNA elucidate molecular networks that cause disease
    • Y. Chen, J. Zhu, and P. Y. Lum et. al. Variations in DNA elucidate molecular networks that cause disease. Nature, 452:429-435, 2008.
    • (2008) Nature , vol.452 , pp. 429-435
    • Chen, Y.1    Zhu, J.2    Lum, P.Y.3
  • 6
    • 85161964661 scopus 로고    scopus 로고
    • Improving posterior marginal approximations in latent Gaussian models
    • B. Cseke and T. Heskes. Improving posterior marginal approximations in latent Gaussian models. In AISTATS, 2010.
    • (2010) AISTATS
    • Cseke, B.1    Heskes, T.2
  • 8
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • J. Fan and R. Li. Variable selection via nonconcave penalized likelihood and its oracle properties. J. of the Am. Stat. Assoc., 96(456):1348-1360, 2001.
    • (2001) J. of the Am. Stat. Assoc. , vol.96 , Issue.456 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 9
    • 0141836275 scopus 로고    scopus 로고
    • Adaptive sparseness for supervised learning
    • M. Figueiredo. Adaptive sparseness for supervised learning. IEEE Trans. on PAMI, 25(9), 2003.
    • (2003) IEEE Trans. on PAMI , vol.25 , Issue.9
    • Figueiredo, M.1
  • 10
    • 84952149204 scopus 로고
    • A statistical view of some chemometrics regression tools
    • I. E. Frank and J. H. Friedman. A statistical view of some chemometrics regression tools. Technometrics, 35(2):109-135, 1993.
    • (1993) Technometrics , vol.35 , Issue.2 , pp. 109-135
    • Frank, I.E.1    Friedman, J.H.2
  • 11
    • 45849134070 scopus 로고    scopus 로고
    • Sparse inverse covariance estimation with the graphical lasso
    • J. Friedman, T. Hastie, and R. Tibshirani. Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9(3), 2008.
    • (2008) Biostatistics , vol.9 , Issue.3
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 13
    • 66449134529 scopus 로고    scopus 로고
    • High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues
    • G. J. Huang, S. Shifman, and W. Valdar et. al. High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues. Genome Research, 19(6):1133-40, 2009.
    • (2009) Genome Research , vol.19 , Issue.6 , pp. 1133-1140
    • Huang, G.J.1    Shifman, S.2    Valdar, W.3
  • 14
    • 84859834457 scopus 로고    scopus 로고
    • On model selection consistency of the elastic net when p ≫ n
    • Department of Statistics
    • J. Jia and B. Yu. On model selection consistency of the elastic net when p ≫ n. Technical Report 756, UC Berkeley, Department of Statistics, 2008.
    • (2008) Technical Report 756, UC Berkeley
    • Jia, J.1    Yu, B.2
  • 15
    • 0022656494 scopus 로고
    • Apolipoprotein e isoforms, serum cholesterol and cancer
    • M. B. Katan. Apolipoprotein E isoforms, serum cholesterol and cancer. Lancet, i:507-508, 1986.
    • (1986) Lancet , vol.1 , pp. 507-508
    • Katan, M.B.1
  • 16
    • 70149098541 scopus 로고    scopus 로고
    • Statistical estimation of correlated genome associations to a quantitative trait network
    • S. Kim and E. Xing. Statistical estimation of correlated genome associations to a quantitative trait network. PLOS Genetics, 5(8), 2009.
    • (2009) PLOS Genetics , vol.5 , Issue.8
    • Kim, S.1    Xing, E.2
  • 17
    • 40849083720 scopus 로고    scopus 로고
    • Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology
    • D. A. Lawlor, R. M. Harbord, and J. Sterne et. al. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat. in Medicine, 27:1133-1163, 2008.
    • (2008) Stat. in Medicine , vol.27 , pp. 1133-1163
    • Lawlor, D.A.1    Harbord, R.M.2    Sterne, J.3
  • 18
    • 62349114549 scopus 로고    scopus 로고
    • Sparse estimation of large covariance matrices via a nested lasso penalty
    • E. Levina, A. Rothman, and J. Zhu. Sparse estimation of large covariance matrices via a nested lasso penalty. The Ann. of App. Stat., 2(1):245-263, 2008.
    • (2008) The Ann. of App. Stat. , vol.2 , Issue.1 , pp. 245-263
    • Levina, E.1    Rothman, A.2    Zhu, J.3
  • 19
    • 69949166983 scopus 로고    scopus 로고
    • Estimating high-dimensional intervention effects from observation data
    • M. H. Maathius, M. Kalisch, and P. Buhlmann. Estimating high-dimensional intervention effects from observation data. The Ann. of Stat., 37:3133-3164, 2009.
    • (2009) The Ann. of Stat. , vol.37 , pp. 3133-3164
    • Maathius, M.H.1    Kalisch, M.2    Buhlmann, P.3
  • 20
    • 0001025418 scopus 로고
    • Bayesian interpolation
    • D. J. C. MacKay. Bayesian interpolation. Neural Computation, 4:415-447, 1992.
    • (1992) Neural Computation , vol.4 , pp. 415-447
    • MacKay, D.J.C.1
  • 22
    • 71149096052 scopus 로고    scopus 로고
    • Regression by dependence minimization and its application to causal inference in additive noise models
    • J. Mooij, D. Janzing, J. Peters, and B. Schoelkopf. Regression by dependence minimization and its application to causal inference in additive noise models. In ICML, 2009.
    • (2009) ICML
    • Mooij, J.1    Janzing, D.2    Peters, J.3    Schoelkopf, B.4
  • 23
    • 0034619331 scopus 로고    scopus 로고
    • A method for fine mapping quantitative trait loci in outbred animal stocks
    • R. Mott, C. J. Talbot, M. G. Turri, A. C. Collins, and J. Flint. A method for fine mapping quantitative trait loci in outbred animal stocks. Proc. Nat. Acad. Sci. USA, 97:12649-12654, 2000.
    • (2000) Proc. Nat. Acad. Sci. USA , vol.97 , pp. 12649-12654
    • Mott, R.1    Talbot, C.J.2    Turri, M.G.3    Collins, A.C.4    Flint, J.5
  • 24
    • 59649099370 scopus 로고    scopus 로고
    • Lean phenotype and resistance to diet-induced obesity in vitamin D receptor knockout mice correlates with induction of uncoupling protein-1
    • C. J. Narvaez and D. Matthews et. al. Lean phenotype and resistance to diet-induced obesity in vitamin D receptor knockout mice correlates with induction of uncoupling protein-1. Endocrinology, 150(2), 2009.
    • (2009) Endocrinology , vol.150 , Issue.2
    • Narvaez, C.J.1    Matthews, D.2
  • 28
    • 77649325496 scopus 로고    scopus 로고
    • Causal inference in statistics: An overview
    • J. Pearl. Causal inference in statistics: an overview. Statistics Surveys, 3:96-146, 2009.
    • (2009) Statistics Surveys , vol.3 , pp. 96-146
    • Pearl, J.1
  • 29
    • 85011121514 scopus 로고    scopus 로고
    • Identification of causal effects using instrumental variables: Comment
    • J. M. Robins and S. Greenland. Identification of causal effects using instrumental variables: comment. J. of the Am. Stat. Assoc., 91:456-458, 1996.
    • (1996) J. of the Am. Stat. Assoc. , vol.91 , pp. 456-458
    • Robins, J.M.1    Greenland, S.2
  • 30
    • 22844446947 scopus 로고    scopus 로고
    • An integrative genomics approach to infer causal associations between gene expression and disease
    • E. E. Schadt, J. Lamb, X. Yang, and J. Zhu et. al. An integrative genomics approach to infer causal associations between gene expression and disease. Nature Genetics, 37(7):710-717, 2005.
    • (2005) Nature Genetics , vol.37 , Issue.7 , pp. 710-717
    • Schadt, E.E.1    Lamb, J.2    Yang, X.3    Zhu, J.4
  • 31
    • 44649181578 scopus 로고    scopus 로고
    • Bayesian inference and optimal design for the sparse linear model
    • M. W. Seeger. Bayesian inference and optimal design for the sparse linear model. JMLR, 9, 2008.
    • (2008) JMLR , vol.9
    • Seeger, M.W.1
  • 32
    • 46149083633 scopus 로고    scopus 로고
    • Identification of conditional interventional distributions
    • I. Shpitser and J. Pearl. Identification of conditional interventional distributions. In UAI, 2006.
    • (2006) UAI
    • Shpitser, I.1    Pearl, J.2
  • 33
    • 33646379109 scopus 로고    scopus 로고
    • Learning the structure of linear latent variable models
    • R. Silva, R. Scheines, C. Glymour, and P. Spirtes. Learning the structure of linear latent variable models. JMLR, 7, 2006.
    • (2006) JMLR , vol.7
    • Silva, R.1    Scheines, R.2    Glymour, C.3    Spirtes, P.4
  • 34
    • 0037322022 scopus 로고    scopus 로고
    • Mendelian randomisation: Can genetic epidemiology contribute to understanding environmental determinants of disease?
    • G. D. Smith and S. Ebrahim. Mendelian randomisation: can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. of Epidemiology, 32:1-22, 2003.
    • (2003) Int. J. of Epidemiology , vol.32 , pp. 1-22
    • Smith, G.D.1    Ebrahim, S.2
  • 35
    • 1942507436 scopus 로고    scopus 로고
    • Commentary: The concept ofMendelian randomization
    • D.C. Thomas and D.V. Conti. Commentary: The concept ofMendelian randomization. Int. J. of Epidemiology, 32, 2004.
    • (2004) Int. J. of Epidemiology , vol.32
    • Thomas, D.C.1    Conti, D.V.2
  • 36
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • R. Tibshirani. Regression shrinkage and selection via the lasso. JRSS B, 58(1):267-288, 1996.
    • (1996) JRSS B , vol.58 , Issue.1 , pp. 267-288
    • Tibshirani, R.1
  • 37
    • 0001224048 scopus 로고    scopus 로고
    • Sparse Bayesian learning and the RVM
    • M. E. Tipping. Sparse Bayesian learning and the RVM. JMLR, 1:211-244, 2001.
    • (2001) JMLR , vol.1 , pp. 211-244
    • Tipping, M.E.1
  • 38
    • 33746540478 scopus 로고    scopus 로고
    • Genome-wide genetic association of complex traits in heterogeneous stock mice
    • W. Valdar, L. C. Solberg, and S. Burnett et. al. Genome-wide genetic association of complex traits in heterogeneous stock mice. Nature Genetics, 38:879-887, 2006.
    • (2006) Nature Genetics , vol.38 , pp. 879-887
    • Valdar, W.1    Solberg, L.C.2    Burnett, S.3
  • 39
    • 65749083666 scopus 로고    scopus 로고
    • Sharp thresholds for high-dimensional and noisy sparsity recovery using L1-constrained quadratic programmming
    • M. Wainwright. Sharp thresholds for high-dimensional and noisy sparsity recovery using L1-constrained quadratic programmming. IEEE Trans. on Inf. Theory, 55:2183-2202, 2007.
    • (2007) IEEE Trans. on Inf. Theory , vol.55 , pp. 2183-2202
    • Wainwright, M.1
  • 40
    • 33847364905 scopus 로고    scopus 로고
    • On the nonnegative garrote estimator
    • M. Yuan and Y. Lin. On the nonnegative garrote estimator. JRSS:B, 69, 2007.
    • (2007) JRSS:B , vol.69
    • Yuan, M.1    Lin, Y.2
  • 41
    • 34247556038 scopus 로고    scopus 로고
    • Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations
    • J. Zhu,M. C.Wiener, and C. Zhang et. al. Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations. PLOS Comp. Biol., 3(4):692-703, 2007.
    • (2007) PLOS Comp. Biol. , vol.3 , Issue.4 , pp. 692-703
    • Zhu, J.1    Wiener, M.C.2    Zhang, C.3
  • 42
    • 16244401458 scopus 로고    scopus 로고
    • Regularization and variable selection via the elastic net
    • H. Zou and T. Hastie. Regularization and variable selection via the elastic net. JRSS:B, 67(2), 2005.
    • (2005) JRSS:B , vol.67 , Issue.2
    • Zou, H.1    Hastie, T.2


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