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The goal of eQTL studies is to identify the genetic variants that influence the expression levels of the genes in an organism.
A note on data-splitting for the evaluation of significance levels
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An improved bonferroni procedure for multiple tests of significance
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Two stage conditionally unbiased estimators of the selected mean
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Controlling the false discovery rate: a practical and powerful approach to multiple testing
Benjamini, Y. and Y. Hochberg (1995) · 1995
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’gene shaving’as a method for identifying distinct sets of genes with similar expression patterns
Hastie, T., R. Tibshirani, M. B. Eisen, A. Alizadeh, R. Levy, L. Staudt, W. C. Chan, D. Botstein, and P. Brown (2000) · 2000
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Genetic dissection of transcriptional regulation in budding yeast
Brem, R. B., G. Yvert, R. Clinton, and L. Kruglyak (2002) · 2002
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Genetics of gene expression surveyed in maize, mouse and man
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Mapping determinants of human gene expression by regional and genome-wide association
Cheung, V. G., R. S. Spielman, K. G. Ewens, T. M. Weber, M. Morley, and J. T. Burdick (2005) · 2005
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Regularization and variable selection via the elastic net
Zou, H. and T. Hastie (2005) · 2005
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Overcoming the winner’s curse: estimating penetrance parameters from case-control data
Zöllner, S. and J. K. Pritchard (2007) · 2007
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Bias-reduced estimators and confidence intervals for odds ratios in genome-wide association studies
Zhong, H. and R. L. Prentice (2008) · 2008
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A unified framework for high-dimensional analysis of m m -estimators with decomposable regularizers
Negahban, S., B. Yu, M. J. Wainwright, and P. K. Ravikumar (2009) · 2009
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Hierarchical clustering with prototypes via minimax linkage
Bien, J. and R. Tibshirani (2011) · 2011
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Tweedie’s formula and selection bias
Efron, B. (2011) · 2011
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Adjusted bayesian inference for selected parameters
Yekutieli, D. (2012) · 2012
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Valid post-selection inference
Berk, R., L. Brown, A. Buja, K. Zhang, L. Zhao, et al. (2013) · 2013
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An empirical bayes approach for multiple tissue eqtl analysis
Li, G., A. A. Shabalin, I. Rusyn, F. A. Wright, and A. B. Nobel (2013) · 2013
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Preserving statistical validity in adaptive data analysis
Dwork, C., V. Feldman, M. Hardt, T. Pitassi, O. Reingold, and A. L. Roth (2015) · 2015
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Fast and efficient qtl mapper for thousands of molecular phenotypes
Ongen, H., A. Buil, A. A. Brown, E. T. Dermitzakis, and O. Delaneau (2015) · 2015
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Exact post-selection inference with the lasso
Lee, J. D., D. L. Sun, Y. Sun, and J. E. Taylor (2016, November) · 2016
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Bayesian post-selection inference in the linear model
Panigrahi, S., J. Taylor, and A. Weinstein (2016) · 2016
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Sparse regression and marginal testing using cluster prototypes
Reid, S. and R. Tibshirani (2016) · 2016
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Exact post-selection inference for sequential regression procedures
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Selection adjusted confidence intervals with more power to determine the sign
Weinstein, A., W. Fithian, and Y. Benjamini (2013) · 2013
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Optimal Inference After Model Selection
Fithian, W., D. Sun, and J. Taylor (2014, October) · 2014
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Exact post model selection inference for marginal screening
Lee, J. D. and J. E. Taylor (2014) · 2014
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A geometric approach to density estimation with additive noise
Wager, S. (2014) · 2014
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The genotype-tissue expression (gtex) pilot analysis: Multitissue gene regulation in humans
Consortium, G. et al. (2015) · 2015
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Tibshirani, R. J., J. Taylor, R. Lockhart, and R. Tibshirani (2016) · 2016
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Testing hypotheses on a tree: new error rates and controlling strategies
Bogomolov, M., C. B. Peterson, Y. Benjamini, and C. Sabatti (2017, May) · 2017
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Genetic effects on gene expression across human tissues
Consortium, G. et al. (2017) · 2017
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Post-selection point and interval estimation of signal sizes in gaussian samples
Reid, S., J. Taylor, and R. Tibshirani (2017) · 2017
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Selective inference with a randomized response
Tian, X., J. Taylor, et al. (2018) · 2018
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The positive false discovery rate: a bayesian interpretation and the q
Storey, J. D. (2003) · 2035
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