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Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model. Chen, Mengjie, Zhao Ren, Hongyu Zhao, and Harrison Zhou. "Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model." J Am Stat Assoc 111, no. 513 (2016): 394-406. Read more about Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model.PubMed
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bcSeq: an R package for fast sequence mapping in high-throughput shRNA and CRISPR screens. Lin, Jiaxing, Jeremy Gresham, Tongrong Wang, So Young Kim, James Alvarez, Jeffrey S. Damrauer, Scott Floyd, Joshua Granek, Andrew Allen, Cliburn Chan et al. "bcSeq: an R package for fast sequence mapping in high-throughput shRNA and CRISPR screens." Bioinformatics 34, no. 20 (2018): 3581-3583. Read more about bcSeq: an R package for fast sequence mapping in high-throughput shRNA and CRISPR screens.PubMed
bcSeq: Fast Sequence Alignment for High-Throughput shRNA and CRISPR Screens (R) bcSeq: Fast Sequence Alignment for High-Throughput shRNA and CRISPR Screens (R)., 2017. Read more about bcSeq: Fast Sequence Alignment for High-Throughput shRNA and CRISPR Screens (R)
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CasANOVA: Simultaneous factor selection and collapsing levels in ANOVA (R). Bondell, Howard D., and Shannon T. Holloway. CasANOVA: Simultaneous factor selection and collapsing levels in ANOVA (R).. R 3.0 ed., 2013. Read more about CasANOVA: Simultaneous factor selection and collapsing levels in ANOVA (R).
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CNVstat: Statistical association analysis of copy number variants (C). Hu, Yi-Juan, Dan-Yu Lin, Wei Sun, and Donglin Zeng. CNVstat: Statistical association analysis of copy number variants (C).. 1.0 ed., 2012. Read more about CNVstat: Statistical association analysis of copy number variants (C).
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Composite large margin classifiers with latent subclasses for heterogeneous biomedical data. Chen, Guanhua, Yufeng Liu, Dinggang Shen, and Michael R. Kosorok. "Composite large margin classifiers with latent subclasses for heterogeneous biomedical data." Stat Anal Data Min 9, no. 2 (2016): 75-88. Read more about Composite large margin classifiers with latent subclasses for heterogeneous biomedical data.PubMed
CONCUR: Kernel-based association test for copy number variation (CNV) aggregate analysis (R) Brucker, Amanda, Shannon T. Holloway, and Jung-Ying Tzeng. CONCUR: Kernel-based association test for copy number variation (CNV) aggregate analysis (R)., 2020. Read more about CONCUR: Kernel-based association test for copy number variation (CNV) aggregate analysis (R)
Consistency and overfitting of multi-omics methods on experimental data. McCabe, Sean D., Dan-Yu Lin, and Michael I. Love. "Consistency and overfitting of multi-omics methods on experimental data." Brief Bioinform 21, no. 4 (2020): 1277-1284. Read more about Consistency and overfitting of multi-omics methods on experimental data.PubMed
Consistent Group Identification and Variable Selection in Regression with Correlated Predictors. Sharma, Dhruv B., Howard D. Bondell, and Hao Helen Zhang. "Consistent Group Identification and Variable Selection in Regression with Correlated Predictors." J Comput Graph Stat 22, no. 2 (2013): 319-340. Read more about Consistent Group Identification and Variable Selection in Regression with Correlated Predictors.PubMed
Consistent high-dimensional Bayesian variable selection via penalized credible regions. Bondell, Howard D., and Brian J. Reich. "Consistent high-dimensional Bayesian variable selection via penalized credible regions." J Am Stat Assoc 107, no. 500 (2012): 1610-1624. Read more about Consistent high-dimensional Bayesian variable selection via penalized credible regions.PubMed
Designing penalty functions in high dimensional problems: The role of tuning parameters. Chen, Ting-Huei, Wei Sun, and Jason P. Fine. "Designing penalty functions in high dimensional problems: The role of tuning parameters." Electron J Stat 10, no. 2 (2016): 2312-2328. Read more about Designing penalty functions in high dimensional problems: The role of tuning parameters.PubMed
Detection of gene-gene interactions using multistage sparse and low-rank regression. Hung, Hung, Yu-Ting Lin, Penweng Chen, Chen-Chien Wang, Su-Yun Huang, and Jung-Ying Tzeng. "Detection of gene-gene interactions using multistage sparse and low-rank regression." Biometrics 72, no. 1 (2016): 85-94. Read more about Detection of gene-gene interactions using multistage sparse and low-rank regression.PubMed
Differential damage and repair of DNA-adducts induced by anti-cancer drug cisplatin across mouse organs. Yimit, Askar, Ogun Adebali, Aziz Sancar, and Yuchao Jiang. "Differential damage and repair of DNA-adducts induced by anti-cancer drug cisplatin across mouse organs." Nat Commun 10, no. 1 (2019): 309. Read more about Differential damage and repair of DNA-adducts induced by anti-cancer drug cisplatin across mouse organs.PubMed
DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors. Walter, Vonn, Andrew B. Nobel, and Fred A. Wright. "DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors." Bioinformatics 27, no. 5 (2011): 678-85. Read more about DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors.PubMed
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Discussion of the Paper by R. L. Prentice and Y. Huang - Optimal Designs and Efficient Inference for Biomarker Studies. Lin, D Y.. "Discussion of the Paper by R. L. Prentice and Y. Huang - Optimal Designs and Efficient Inference for Biomarker Studies." Stat Theory Relat Fields 2, no. 1 (2018): 21-22. Read more about Discussion of the Paper by R. L. Prentice and Y. Huang - Optimal Designs and Efficient Inference for Biomarker Studies.PubMed
Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction. Chen, Jingxiang, Chong Zhang, Michael R. Kosorok, and Yufeng Liu. "Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction." Stat Interface 11, no. 3 (2018): 401-420. Read more about Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction.PubMed
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Effective SNP ranking improves the performance of eQTL mapping. X Jeng, Jessie, Jacob Rhyne, Teng Zhang, and Jung-Ying Tzeng. "Effective SNP ranking improves the performance of eQTL mapping." Genet Epidemiol 44, no. 6 (2020): 611-619. Read more about Effective SNP ranking improves the performance of eQTL mapping.PubMed
Efficient Estimation for Semiparametric Structural Equation Models With Censored Data. Wong, Kin Yau, Donglin Zeng, and D Y. Lin. "Efficient Estimation for Semiparametric Structural Equation Models With Censored Data." J Am Stat Assoc 113, no. 522 (2018): 893-905. Read more about Efficient Estimation for Semiparametric Structural Equation Models With Censored Data.PubMed
Efficient estimation of grouped survival models. Li, Zhiguo, Jiaxing Lin, Alexander B. Sibley, Tracy Truong, Katherina C. Chua, Yu Jiang, Janice McCarthy, Deanna L. Kroetz, Andrew Allen, and Kouros Owzar. "Efficient estimation of grouped survival models." BMC Bioinformatics 20, no. 1 (2019): 269. Read more about Efficient estimation of grouped survival models.PubMed
Efficient Estimation of Semiparametric Transformation Models for the Cumulative Incidence of Competing Risks. Mao, Lu, and D Y. Lin. "Efficient Estimation of Semiparametric Transformation Models for the Cumulative Incidence of Competing Risks." J R Stat Soc Series B Stat Methodol 79, no. 2 (2017): 573-587. Read more about Efficient Estimation of Semiparametric Transformation Models for the Cumulative Incidence of Competing Risks.PubMed
Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data. Diao, Guoqing, Donglin Zeng, and Song Yang. "Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data." Biometrics 69, no. 4 (2013): 840-9. Read more about Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data.PubMed
Efficient Semiparametric Inference Under Two-Phase Sampling, With Applications to Genetic Association Studies. Tao, Ran, Donglin Zeng, and Dan-Yu Lin. "Efficient Semiparametric Inference Under Two-Phase Sampling, With Applications to Genetic Association Studies." J Am Stat Assoc 112, no. 520 (2017): 1468-1476. Read more about Efficient Semiparametric Inference Under Two-Phase Sampling, With Applications to Genetic Association Studies.PubMed
Efficient Signal Inclusion With Genomic Applications. X Jeng, Jessie, Teng Zhang, and Jung-Ying Tzeng. "Efficient Signal Inclusion With Genomic Applications." J Am Stat Assoc 114, no. 528 (2019): 1787-1799. Read more about Efficient Signal Inclusion With Genomic Applications.PubMed
Efficient test-based variable selection for high-dimensional linear models. Gong, Siliang, Kai Zhang, and Yufeng Liu. "Efficient test-based variable selection for high-dimensional linear models." J Multivar Anal 166 (2018): 17-31. Read more about Efficient test-based variable selection for high-dimensional linear models.PubMed
Empirical pathway analysis, without permutation. Zhou, Yi-Hui, William T. Barry, and Fred A. Wright. "Empirical pathway analysis, without permutation." Biostatistics 14, no. 3 (2013): 573-85. Read more about Empirical pathway analysis, without permutation.PubMed
Establishment of reference standards in biosimilar studies. Zhang, Aijing, Jung-Ying Tzeng, and Shein-Chung Chow. "Establishment of reference standards in biosimilar studies." GaBI J 2, no. 4 (2013): 173-177. Read more about Establishment of reference standards in biosimilar studies.PubMed
Estimating individualized treatment rules for ordinal treatments. Chen, Jingxiang, Haoda Fu, Xuanyao He, Michael R. Kosorok, and Yufeng Liu. "Estimating individualized treatment rules for ordinal treatments." Biometrics 74, no. 3 (2018): 924-933. Read more about Estimating individualized treatment rules for ordinal treatments.PubMed
Estimating Individualized Treatment Rules Using Outcome Weighted Learning. Zhao, Yingqi, Donglin Zeng, John A Rush, and Michael R. Kosorok. "Estimating Individualized Treatment Rules Using Outcome Weighted Learning." J Am Stat Assoc 107, no. 449 (2012): 1106-1118. Read more about Estimating Individualized Treatment Rules Using Outcome Weighted Learning.PubMed
Evaluating haplotype effects in case-control studies via penalized-likelihood approaches: prospective or retrospective analysis? Koehler, Megan L., Howard D. Bondell, and Jung-Ying Tzeng. "Evaluating haplotype effects in case-control studies via penalized-likelihood approaches: prospective or retrospective analysis?" Genet Epidemiol 34, no. 8 (2010): 892-911. Read more about Evaluating haplotype effects in case-control studies via penalized-likelihood approaches: prospective or retrospective analysis?PubMed
Exploiting expression patterns across multiple tissues to map expression quantitative trait loci. Acharya, Chaitanya R., Janice M. McCarthy, Kouros Owzar, and Andrew S. Allen. "Exploiting expression patterns across multiple tissues to map expression quantitative trait loci." BMC Bioinformatics 17 (2016): 257. Read more about Exploiting expression patterns across multiple tissues to map expression quantitative trait loci.PubMed
Facilitating the Calculation of the Efficient Score Using Symbolic Computing. Sibley, Alexander, Zhiguo Li, Yu Jiang, Yi-Ju Li, Cliburn Chan, Andrew Allen, and Kouros Owzar. "Facilitating the Calculation of the Efficient Score Using Symbolic Computing." Am Stat 72, no. 2 (2018): 199-205. Read more about Facilitating the Calculation of the Efficient Score Using Symbolic Computing.PubMed
False discovery rate control for high dimensional networks of quantile associations conditioning on covariates. Xie, Jichun, and Ruosha Li. "False discovery rate control for high dimensional networks of quantile associations conditioning on covariates." J R Stat Soc Series B Stat Methodol 80, no. 5 (2018): 1015-1034. Read more about False discovery rate control for high dimensional networks of quantile associations conditioning on covariates.PubMed
Fast Bayesian Variable Screenings for Binary Response Regressions with Small Sample Size. Chang, S-M, J-Y Tzeng, and R-B Chen. "Fast Bayesian Variable Screenings for Binary Response Regressions with Small Sample Size." J Stat Comput Simul 87, no. 14 (2017): 2708-2723. Read more about Fast Bayesian Variable Screenings for Binary Response Regressions with Small Sample Size.PubMed
fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies. Lin, Jiaxing, Alexander Sibley, Ivo Shterev, Andrew Nixon, Federico Innocenti, Cliburn Chan, and Kouros Owzar. "fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies." BMC Bioinformatics 20, no. 1 (2019): 333. Read more about fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies.PubMed
FastKM: A fast multiple-kernel method based on a low-rank approximation (R). Marceau, Rachel, Wenbin Lu, Michèle M. Sale, Bradford B. Worrall, Stephen R. Williams, Fang-Chi Hsu, Jung-Ying Tzeng, and Shannon T. Holloway. FastKM: A fast multiple-kernel method based on a low-rank approximation (R).. 1.0 ed., 2015. Read more about FastKM: A fast multiple-kernel method based on a low-rank approximation (R).
FEATURE ELIMINATION IN KERNEL MACHINES IN MODERATELY HIGH DIMENSIONS. Dasgupta, Sayan, Yair Goldberg, and Michael R. Kosorok. "FEATURE ELIMINATION IN KERNEL MACHINES IN MODERATELY HIGH DIMENSIONS." Ann Stat 47, no. 1 (2019): 497-526. Read more about FEATURE ELIMINATION IN KERNEL MACHINES IN MODERATELY HIGH DIMENSIONS.PubMed
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Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood. Li, Zhiguo, and Kouros Owzar. "Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood." Scand Stat Theory Appl 43, no. 2 (2016): 476-486. Read more about Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood.PubMed
Gene selection using iterative feature elimination random forests for survival outcomes. Pang, Herbert, Stephen L. George, Ken Hui, and Tiejun Tong. "Gene selection using iterative feature elimination random forests for survival outcomes." IEEE/ACM Trans Comput Biol Bioinform 9, no. 5 (2012): 1422-31. Read more about Gene selection using iterative feature elimination random forests for survival outcomes.PubMed
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GENE-LEVEL PHARMACOGENETIC ANALYSIS ON SURVIVAL OUTCOMES USING GENE-TRAIT SIMILARITY REGRESSION. Tzeng, Jung-Ying, Wenbin Lu, and Fang-Chi Hsu. "GENE-LEVEL PHARMACOGENETIC ANALYSIS ON SURVIVAL OUTCOMES USING GENE-TRAIT SIMILARITY REGRESSION." Ann Appl Stat 8, no. 2 (2014): 1232-1255. Read more about GENE-LEVEL PHARMACOGENETIC ANALYSIS ON SURVIVAL OUTCOMES USING GENE-TRAIT SIMILARITY REGRESSION.PubMed
geneSelRSF: Gene selection using iterative recursive feature elimination (R). Pang, Herbert. geneSelRSF: Gene selection using iterative recursive feature elimination (R).. 1.0 ed., 2012. Read more about geneSelRSF: Gene selection using iterative recursive feature elimination (R).
Genetic analyses of diverse populations improves discovery for complex traits. Wojcik, Genevieve L., Mariaelisa Graff, Katherine K. Nishimura, Ran Tao, Jeffrey Haessler, Christopher R. Gignoux, Heather M. Highland, Yesha M. Patel, Elena P. Sorokin, Christy L. Avery et al. "Genetic analyses of diverse populations improves discovery for complex traits." Nature 570, no. 7762 (2019): 514-518. Read more about Genetic analyses of diverse populations improves discovery for complex traits.PubMed
Genetic association analysis under complex survey sampling: the Hispanic Community Health Study/Study of Latinos. Lin, Dan-Yu, Ran Tao, William D. Kalsbeek, Donglin Zeng, Franklyn Gonzalez, Lindsay Fernández-Rhodes, Mariaelisa Graff, Gary G. Koch, Kari E. North, and Gerardo Heiss. "Genetic association analysis under complex survey sampling: the Hispanic Community Health Study/Study of Latinos." Am J Hum Genet 95, no. 6 (2014): 675-88. Read more about Genetic association analysis under complex survey sampling: the Hispanic Community Health Study/Study of Latinos.PubMed
Genome analysis and pleiotropy assessment using causal networks with loss of function mutation and metabolomics. Yazdani, Azam, Akram Yazdani, Sarah H. Elsea, Daniel J. Schaid, Michael R. Kosorok, Gita Dangol, and Ahmad Samiei. "Genome analysis and pleiotropy assessment using causal networks with loss of function mutation and metabolomics." BMC Genomics 20, no. 1 (2019): 395. Read more about Genome analysis and pleiotropy assessment using causal networks with loss of function mutation and metabolomics.PubMed
Genome-wide association study identifies five new schizophrenia loci. "Genome-wide association study identifies five new schizophrenia loci." Nat Genet 43, no. 10 (2011): 969-76. Read more about Genome-wide association study identifies five new schizophrenia loci.PubMed
Global copy number profiling of cancer genomes. Wang, Xuefeng, Mengjie Chen, Xiaoqing Yu, Natapol Pornputtapong, Hao Chen, Nancy R. Zhang, Scott R Powers, and Michael Krauthammer. "Global copy number profiling of cancer genomes." Bioinformatics 32, no. 6 (2016): 926-8. Read more about Global copy number profiling of cancer genomes.PubMed
Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example. Hidalgo, Sebastian J. Teran, Michael C. Wu, Stephanie M. Engel, and Michael R. Kosorok. "Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example." Comput Stat Data Anal 122 (2018): 135-155. Read more about Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example.PubMed
groupedSurv: Efficient Estimation of Grouped Survival Models Using the Exact Likelihood Function (R) Lin, Jiaxing, Alexander Sibley, Tracy Truong, Kouros Owzar, and Zhiguo Li. groupedSurv: Efficient Estimation of Grouped Survival Models Using the Exact Likelihood Function (R). 1.0.0 ed., 2018. Read more about groupedSurv: Efficient Estimation of Grouped Survival Models Using the Exact Likelihood Function (R)
GWASelect: A variable selection method for genomewide association studies (C++). He, Qianchuan, and Dan-Yu Lin. GWASelect: A variable selection method for genomewide association studies (C++).., 2011. Read more about GWASelect: A variable selection method for genomewide association studies (C++).
Haplo.CasGLM: Haplotype specific simultaneous factor selection and collapsing levels in GLM (R). Bondell, Howard D., Jung-Ying Tzeng, Megan L. Koehler, and Shannon T. Holloway. Haplo.CasGLM: Haplotype specific simultaneous factor selection and collapsing levels in GLM (R).. 3rd ed., 2013. Read more about Haplo.CasGLM: Haplotype specific simultaneous factor selection and collapsing levels in GLM (R).
Hard or Soft Classification? Large-margin Unified Machines. Liu, Yufeng, Hao Helen Zhang, and Yichao Wu. "Hard or Soft Classification? Large-margin Unified Machines." J Am Stat Assoc 106, no. 493 (2011): 166-177. Read more about Hard or Soft Classification? Large-margin Unified Machines.PubMed
Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. Zhu, Anqi, Joseph G. Ibrahim, and Michael I. Love. "Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences." Bioinformatics 35, no. 12 (2019): 2084-2092. Read more about Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences.PubMed
highTtest: Simultaneous critical values for t-tests in very high dimensions (R). Cao, Hongyuan, Michael R. Kosorok, and Shannon T. Holloway. highTtest: Simultaneous critical values for t-tests in very high dimensions (R).. 1.0 ed., 2014. Read more about highTtest: Simultaneous critical values for t-tests in very high dimensions (R).
HSSVD: Biclustering with heterogeneous variance (R). Chen, Guanhua, and Michael R. Kosorok. HSSVD: Biclustering with heterogeneous variance (R).., 2013. Read more about HSSVD: Biclustering with heterogeneous variance (R).
Hypothesis testing at the extremes: fast and robust association for high-throughput data. Zhou, Yi-Hui, and Fred A. Wright. "Hypothesis testing at the extremes: fast and robust association for high-throughput data." Biostatistics 16, no. 3 (2015): 611-25. Read more about Hypothesis testing at the extremes: fast and robust association for high-throughput data.PubMed
Hypothesis testing for band size detection of high-dimensional banded precision matrices. An, Baiguo, Jianhua Guo, and Yufeng Liu. "Hypothesis testing for band size detection of high-dimensional banded precision matrices." Biometrika 101, no. 2 (2014): 477-483. Read more about Hypothesis testing for band size detection of high-dimensional banded precision matrices.PubMed
I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms. Wong, Kin Yau, Cheng Fan, Maki Tanioka, Joel S. Parker, Andrew B. Nobel, Donglin Zeng, Dan-Yu Lin, and Charles M. Perou. "I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms." Genome Biol 20, no. 1 (2019): 52. Read more about I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms.PubMed
Identification of predictive pathways for non-hodgkin lymphoma prognosis. Han, Xuesong, Yang Li, Jian Huang, Yawei Zhang, Theodore Holford, Qing Lan, Nathaniel Rothman, Tongzhang Zheng, Michael R. Kosorok, and Shuangge Ma. "Identification of predictive pathways for non-hodgkin lymphoma prognosis." Cancer Inform 9 (2010): 281-92. Read more about Identification of predictive pathways for non-hodgkin lymphoma prognosis.PubMed
Identifying individual risk rare variants using protein structure guided local tests (POINT). West, Rachel Marceau, Wenbin Lu, Daniel M. Rotroff, Melaine A. Kuenemann, Sheng-Mao Chang, Michael C. Wu, Michael J. Wagner, John B. Buse, Alison A. Motsinger-Reif, Denis Fourches et al. "Identifying individual risk rare variants using protein structure guided local tests (POINT)." PLoS Comput Biol 15, no. 2 (2019): e1006722. Read more about Identifying individual risk rare variants using protein structure guided local tests (POINT).PubMed
Incorporating Functional Information in Tests of Excess De Novo Mutational Load. Jiang, Yu, Yujun Han, Slavé Petrovski, Kouros Owzar, David B. Goldstein, and Andrew S. Allen. "Incorporating Functional Information in Tests of Excess De Novo Mutational Load." Am J Hum Genet 97, no. 2 (2015): 272-83. Read more about Incorporating Functional Information in Tests of Excess De Novo Mutational Load.PubMed
Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis. Ma, Shuangge, Michael R. Kosorok, Jian Huang, and Ying Dai. "Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis." BMC Med Genomics 4 (2011): 5. Read more about Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis.PubMed
Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules. Butler, Emily L., Eric B. Laber, Sonia M. Davis, and Michael R. Kosorok. "Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules." Biometrics 74, no. 1 (2018): 18-26. Read more about Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules.PubMed
Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks. Xue, Hongqi, Shuang Wu, Yichao Wu, Juan C. Ramirez Idarraga, and Hulin Wu. "Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks." Stat Med 37, no. 17 (2018): 2630-2644. Read more about Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks.PubMed
Inference on phenotype-specific effects of genes using multivariate kernel machine regression. Maity, Arnab, Jing Zhao, Patrick F. Sullivan, and Jung-Ying Tzeng. "Inference on phenotype-specific effects of genes using multivariate kernel machine regression." Genet Epidemiol 42, no. 1 (2018): 64-79. Read more about Inference on phenotype-specific effects of genes using multivariate kernel machine regression.PubMed
IntCens: Nonparametric maximum likelihood estimation for a broad class of semiparametric regression models with general interval-censored data (R). Bunn, Paul, Donglin Zeng, and Dan-Yu Lin. IntCens: Nonparametric maximum likelihood estimation for a broad class of semiparametric regression models with general interval-censored data (R).., 2016. Read more about IntCens: Nonparametric maximum likelihood estimation for a broad class of semiparametric regression models with general interval-censored data (R).
intcensROC: Fast Spline Function Based Constrained Maximum Likelihood Estimator for AUC Estimation of Interval Censored Survival Data (R) Lin, Jiaxing, Yuan Wu, Xiaofei F. Wang, and Kouros Owzar. intcensROC: Fast Spline Function Based Constrained Maximum Likelihood Estimator for AUC Estimation of Interval Censored Survival Data (R). 0.1.1 ed., 2018. Read more about intcensROC: Fast Spline Function Based Constrained Maximum Likelihood Estimator for AUC Estimation of Interval Censored Survival Data (R)
Integrative analysis of sequencing and array genotype data for discovering disease associations with rare mutations. Hu, Yi-Juan, Yun Li, Paul L. Auer, and Dan-Yu Lin. "Integrative analysis of sequencing and array genotype data for discovering disease associations with rare mutations." Proc Natl Acad Sci U S A 112, no. 4 (2015): 1019-24. Read more about Integrative analysis of sequencing and array genotype data for discovering disease associations with rare mutations.PubMed
Integrative gene set analysis of multi-platform data with sample heterogeneity. Hu, Jun, and Jung-Ying Tzeng. "Integrative gene set analysis of multi-platform data with sample heterogeneity." Bioinformatics 30, no. 11 (2014): 1501-7. Read more about Integrative gene set analysis of multi-platform data with sample heterogeneity.PubMed
Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny. Urrutia, Eugene, Hao Chen, Zilu Zhou, Nancy R. Zhang, and Yuchao Jiang. "Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny." Bioinformatics 34, no. 12 (2018): 2126-2128. Read more about Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny.PubMed
Intergenerational response to the endocrine disruptor vinclozolin is influenced by maternal genotype and crossing scheme. Pietryk, Edward W., Kiristin Clement, Marwa Elnagheeb, Ryan Kuster, Kayla Kilpatrick, Michael I. Love, and Folami Y. Ideraabdullah. "Intergenerational response to the endocrine disruptor vinclozolin is influenced by maternal genotype and crossing scheme." Reprod Toxicol 78 (2018): 9-19. Read more about Intergenerational response to the endocrine disruptor vinclozolin is influenced by maternal genotype and crossing scheme.PubMed
Inverse regression estimation for censored data. Nadkarni, Nivedita V., Yingqi Zhao, and Michael R. Kosorok. "Inverse regression estimation for censored data." J Am Stat Assoc 106, no. 493 (2011): 178-190. Read more about Inverse regression estimation for censored data.PubMed
JAGUAR: Joint analysis of genotype and group-specific variability using a novel score test approach to map expression quantitative trait loci (eQTL) (R) Acharya, Chaitanya R., Janice M. McCarthy, Kouros Owzar, and Andrew S. Allen. JAGUAR: Joint analysis of genotype and group-specific variability using a novel score test approach to map expression quantitative trait loci (eQTL) (R). 3.0.1 ed., 2016. Read more about JAGUAR: Joint analysis of genotype and group-specific variability using a novel score test approach to map expression quantitative trait loci (eQTL) (R)
Joint Estimation of Multiple Precision Matrices with Common Structures. Lee, Wonyul, and Yufeng Liu. "Joint Estimation of Multiple Precision Matrices with Common Structures." J Mach Learn Res 16 (2015): 1035-1062. Read more about Joint Estimation of Multiple Precision Matrices with Common Structures.PubMed
Joint skeleton estimation of multiple directed acyclic graphs for heterogeneous population. Liu, Jianyu, Wei Sun, and Yufeng Liu. "Joint skeleton estimation of multiple directed acyclic graphs for heterogeneous population." Biometrics 75, no. 1 (2019): 36-47. Read more about Joint skeleton estimation of multiple directed acyclic graphs for heterogeneous population.PubMed
Latent Supervised Learning. Wei, Susan, and Michael R. Kosorok. "Latent Supervised Learning." J Am Stat Assoc 108, no. 503 (2013). Read more about Latent Supervised Learning.PubMed
Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models. Zhang, Hao Helen, Guang Cheng, and Yufeng Liu. "Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models." J Am Stat Assoc 106, no. 495 (2011): 1099-1112. Read more about Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models.PubMed
LOCAL INDEPENDENCE FEATURE SCREENING FOR NONPARAMETRIC AND SEMIPARAMETRIC MODELS BY MARGINAL EMPIRICAL LIKELIHOOD. Chang, Jinyuan, Cheng Yong Tang, and Yichao Wu. "LOCAL INDEPENDENCE FEATURE SCREENING FOR NONPARAMETRIC AND SEMIPARAMETRIC MODELS BY MARGINAL EMPIRICAL LIKELIHOOD." Ann Stat 44, no. 2 (2016): 515-539. Read more about LOCAL INDEPENDENCE FEATURE SCREENING FOR NONPARAMETRIC AND SEMIPARAMETRIC MODELS BY MARGINAL EMPIRICAL LIKELIHOOD.PubMed
Mapping eQTL by leveraging multiple tissues and DNA methylation. Acharya, Chaitanya R., Kouros Owzar, and Andrew S. Allen. "Mapping eQTL by leveraging multiple tissues and DNA methylation." BMC Bioinformatics 18, no. 1 (2017): 455. Read more about Mapping eQTL by leveraging multiple tissues and DNA methylation.PubMed
MARATHON: Integrates Multiple Related Statistical Software for Copy Number Profiling and Downstream Analyses (R) Urrutia, Eugene, Hao Chen, Zilu Zhou, Nancy R. Zhang, and Yuchao Jiang. MARATHON: Integrates Multiple Related Statistical Software for Copy Number Profiling and Downstream Analyses (R)., 2018. Read more about MARATHON: Integrates Multiple Related Statistical Software for Copy Number Profiling and Downstream Analyses (R)
MASS: meta-analysis of score statistics for sequencing studies. Tang, Zheng-Zheng, and Dan-Yu Lin. "MASS: meta-analysis of score statistics for sequencing studies." Bioinformatics 29, no. 14 (2013): 1803-5. Read more about MASS: meta-analysis of score statistics for sequencing studies.PubMed
MASS: Meta-analysis of sequencing studies (C). Tang, Zheng-Zheng, and Dan-Yu Lin. MASS: Meta-analysis of sequencing studies (C).. 5.0 ed., 2013. Read more about MASS: Meta-analysis of sequencing studies (C).
Maximum likelihood estimation for semiparametric regression models with multivariate interval-censored data. Zeng, Donglin, Fei Gao, and D Y. Lin. "Maximum likelihood estimation for semiparametric regression models with multivariate interval-censored data." Biometrika 104, no. 3 (2017): 505-525. Read more about Maximum likelihood estimation for semiparametric regression models with multivariate interval-censored data.PubMed
Maximum likelihood estimation for semiparametric transformation models with interval-censored data. Zeng, Donglin, Lu Mao, and D Y. Lin. "Maximum likelihood estimation for semiparametric transformation models with interval-censored data." Biometrika 103, no. 2 (2016): 253-271. Read more about Maximum likelihood estimation for semiparametric transformation models with interval-censored data.PubMed
Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs. Tang, Zheng-Zheng, and Dan-Yu Lin. "Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs." Am J Hum Genet 97, no. 1 (2015): 35-53. Read more about Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs.PubMed
Meta-analysis of gene-level associations for rare variants based on single-variant statistics. Hu, Yi-Juan, Sonja I. Berndt, Stefan Gustafsson, Andrea Ganna, Joel Hirschhorn, Kari E. North, Erik Ingelsson, and Dan-Yu Lin. "Meta-analysis of gene-level associations for rare variants based on single-variant statistics." Am J Hum Genet 93, no. 2 (2013): 236-48. Read more about Meta-analysis of gene-level associations for rare variants based on single-variant statistics.PubMed
Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data. Lin, D Y., and D Zeng. "Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data." Genet Epidemiol 34, no. 1 (2010): 60-6. Read more about Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data.PubMed
Meta-analysis of sequencing studies with heterogeneous genetic associations. Tang, Zheng-Zheng, and Dan-Yu Lin. "Meta-analysis of sequencing studies with heterogeneous genetic associations." Genet Epidemiol 38, no. 5 (2014): 389-401. Read more about Meta-analysis of sequencing studies with heterogeneous genetic associations.PubMed
Module-based association analysis for omics data with network structure. Wang, Zhi, Arnab Maity, Chuhsing Kate Hsiao, Deepak Voora, Rima Kaddurah-Daouk, and Jung-Ying Tzeng. "Module-based association analysis for omics data with network structure." PLoS One 10, no. 3 (2015): e0122309. Read more about Module-based association analysis for omics data with network structure.PubMed
MOST: Multivariate outcome score test (C). He, Qianchuan, and Dan-Yu Lin. MOST: Multivariate outcome score test (C).. 1.0 ed., 2013. Read more about MOST: Multivariate outcome score test (C).
Multicategory angle-based large-margin classification. Zhang, Chong, and Yufeng Liu. "Multicategory angle-based large-margin classification." Biometrika 101, no. 3 (2014): 625-640. Read more about Multicategory angle-based large-margin classification.PubMed
Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration. Chen, Tianle, Donglin Zeng, and Yuanjia Wang. "Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration." Biometrics 71, no. 4 (2015): 918-28. Read more about Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration.PubMed
Multiple testing for gene sets from microarray experiments. Sohn, Insuk, Kouros Owzar, Johan Lim, Stephen L. George, Stephanie Mackey Cushman, and Sin-Ho Jung. "Multiple testing for gene sets from microarray experiments." BMC Bioinformatics 12 (2011): 209. Read more about Multiple testing for gene sets from microarray experiments.PubMed
Multisensory Logic of Infant-Directed Aggression by Males. Isogai, Yoh, Zheng Wu, Michael I. Love, Michael Ho- Young Ahn, Dhananjay Bambah-Mukku, Vivian Hua, Karolina Farrell, and Catherine Dulac. "Multisensory Logic of Infant-Directed Aggression by Males." Cell 175, no. 7 (2018): 1827-1841.e17. Read more about Multisensory Logic of Infant-Directed Aggression by Males.PubMed
MultiTDS: Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling (C++) Tao, Ran, Donglin Zeng, Nora Franceschini, Kari E. North, Eric Boerwinkle, and Dan-Yu Lin. MultiTDS: Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling (C++)., 2015. Read more about MultiTDS: Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling (C++)
Multivariate phenotype association analysis by marker-set kernel machine regression. Maity, Arnab, Patrick F. Sullivan, and Jun-Ying Tzeng. "Multivariate phenotype association analysis by marker-set kernel machine regression." Genet Epidemiol 36, no. 7 (2012): 686-95. Read more about Multivariate phenotype association analysis by marker-set kernel machine regression.PubMed
Nomenclature for alleles of the thiopurine methyltransferase gene. Appell, Malin L., Jonathan Berg, John Duley, William E. Evans, Martin A. Kennedy, Lynne Lennard, Tony Marinaki, Howard L. McLeod, Mary V. Relling, Elke Schaeffeler et al. "Nomenclature for alleles of the thiopurine methyltransferase gene." Pharmacogenet Genomics 23, no. 4 (2013): 242-8. Read more about Nomenclature for alleles of the thiopurine methyltransferase gene.PubMed
Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications. Van den Berge, Koen, Fanny Perraudeau, Charlotte Soneson, Michael I. Love, Davide Risso, Jean-Philippe Vert, Mark D. Robinson, Sandrine Dudoit, and Lieven Clement. "Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications." Genome Biol 19, no. 1 (2018): 24. Read more about Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.PubMed
On Quantile Regression in Reproducing Kernel Hilbert Spaces with Data Sparsity Constraint. Zhang, Chong, Yufeng Liu, and Yichao Wu. "On Quantile Regression in Reproducing Kernel Hilbert Spaces with Data Sparsity Constraint." J Mach Learn Res 17, no. 40 (2016): 1-45. Read more about On Quantile Regression in Reproducing Kernel Hilbert Spaces with Data Sparsity Constraint.PubMed
On the Aggregation of Multimarker Information for Marker-Set and Sequencing Data Analysis: Genotype Collapsing vs. Similarity Collapsing. Pongpanich, Monnat, Megan L. Neely, and Jung-Ying Tzeng. "On the Aggregation of Multimarker Information for Marker-Set and Sequencing Data Analysis: Genotype Collapsing vs. Similarity Collapsing." Front Genet 2 (2011): 110. Read more about On the Aggregation of Multimarker Information for Marker-Set and Sequencing Data Analysis: Genotype Collapsing vs. Similarity Collapsing.PubMed
On the relative efficiency of using summary statistics versus individual-level data in meta-analysis. Lin, D Y., and D Zeng. "On the relative efficiency of using summary statistics versus individual-level data in meta-analysis." Biometrika 97, no. 2 (2010): 321-332. Read more about On the relative efficiency of using summary statistics versus individual-level data in meta-analysis.PubMed
On the substructure controls in rare variant analysis: Principal components or variance components? Luo, Yiwen, Arnab Maity, Michael C. Wu, Chris Smith, Qing Duan, Yun Li, and Jung-Ying Tzeng. "On the substructure controls in rare variant analysis: Principal components or variance components?" Genet Epidemiol 42, no. 3 (2018): 276-287. Read more about On the substructure controls in rare variant analysis: Principal components or variance components?PubMed
Pathway-based identification of SNPs predictive of survival. Pang, Herbert, Michael Hauser, and Stéphane Minvielle. "Pathway-based identification of SNPs predictive of survival." Eur J Hum Genet 19, no. 6 (2011): 704-9. Read more about Pathway-based identification of SNPs predictive of survival.PubMed
Pathway-guided identification of gene-gene interactions. Wang, Xin, Daowen Zhang, and Jung-Ying Tzeng. "Pathway-guided identification of gene-gene interactions." Ann Hum Genet 78, no. 6 (2014): 478-91. Read more about Pathway-guided identification of gene-gene interactions.PubMed
Penalized nonlinear mixed effects model to identify biomarkers that predict disease progression. Chen, Huaihou, Donglin Zeng, and Yuanjia Wang. "Penalized nonlinear mixed effects model to identify biomarkers that predict disease progression." Biometrics 73, no. 4 (2017): 1343-1354. Read more about Penalized nonlinear mixed effects model to identify biomarkers that predict disease progression.PubMed
permGPU: Using graphics processing units in RNA microarray association studies (CUDA). Shterev, Ivo D., Sin-Ho Jung, Stephen L. George, and Kouros Owzar. permGPU: Using graphics processing units in RNA microarray association studies (CUDA).., 2011. Read more about permGPU: Using graphics processing units in RNA microarray association studies (CUDA).
permGPU: Using graphics processing units in RNA microarray association studies. Shterev, Ivo D., Sin-Ho Jung, Stephen L. George, and Kouros Owzar. "permGPU: Using graphics processing units in RNA microarray association studies." BMC Bioinformatics 11 (2010): 329. Read more about permGPU: Using graphics processing units in RNA microarray association studies.PubMed
Pharmacogenetics, enzyme probes and therapeutic drug monitoring as potential tools for individualizing taxane therapy. Krens, Stefanie D., Howard L. McLeod, and Daniel L. Hertz. "Pharmacogenetics, enzyme probes and therapeutic drug monitoring as potential tools for individualizing taxane therapy." Pharmacogenomics 14, no. 5 (2013): 555-74. Read more about Pharmacogenetics, enzyme probes and therapeutic drug monitoring as potential tools for individualizing taxane therapy.PubMed
Pharmacogenomics as a risk mitigation strategy for chemotherapeutic cardiotoxicity. Jensen, Brian C., and Howard L. McLeod. "Pharmacogenomics as a risk mitigation strategy for chemotherapeutic cardiotoxicity." Pharmacogenomics 14, no. 2 (2013): 205-13. Read more about Pharmacogenomics as a risk mitigation strategy for chemotherapeutic cardiotoxicity.PubMed
PICAFT: Semiparametric Estimation of the Accelerated Failure Time Model With Partly Interval-Censored Data (R) Gao, Fei, Donglin Zeng, and Dan-Yu Lin. PICAFT: Semiparametric Estimation of the Accelerated Failure Time Model With Partly Interval-Censored Data (R)., 2017. Read more about PICAFT: Semiparametric Estimation of the Accelerated Failure Time Model With Partly Interval-Censored Data (R)
POINT: Protein Structure Guided Local Test (R) West, Rachel Marceau, and Shannon T. Holloway. POINT: Protein Structure Guided Local Test (R). 1.0 ed., 2019. Read more about POINT: Protein Structure Guided Local Test (R)
Posterior Contraction Rates of the Phylogenetic Indian Buffet Processes. Chen, Mengjie, Chao Gao, and Hongyu Zhao. "Posterior Contraction Rates of the Phylogenetic Indian Buffet Processes." Bayesian Anal 11, no. 2 (2016): 477-497. Read more about Posterior Contraction Rates of the Phylogenetic Indian Buffet Processes.PubMed
Power and sample size calculation for microarray studies. Jung, Sin-Ho, and Stanley S Young. "Power and sample size calculation for microarray studies." J Biopharm Stat 22, no. 1 (2012): 30-42. Read more about Power and sample size calculation for microarray studies.PubMed
Power and sample size calculations for SNP association studies with censored time-to-event outcomes. Owzar, Kouros, Zhiguo Li, Nancy Cox, and Sin-Ho Jung. "Power and sample size calculations for SNP association studies with censored time-to-event outcomes." Genet Epidemiol 36, no. 6 (2012): 538-48. Read more about Power and sample size calculations for SNP association studies with censored time-to-event outcomes.PubMed
Precision Medicine. Kosorok, Michael R., and Eric B. Laber. "Precision Medicine." Annu Rev Stat Appl 6 (2019): 263-286. Read more about Precision Medicine.PubMed
Predicting Alzheimer's Disease Using Combined Imaging-Whole Genome SNP Data. Kong, Dehan, Kelly S. Giovanello, Yalin Wang, Weili Lin, Eunjee Lee, Yong Fan, Murali P Doraiswamy, and Hongtu Zhu. "Predicting Alzheimer's Disease Using Combined Imaging-Whole Genome SNP Data." J Alzheimers Dis 46, no. 3 (2015): 695-702. Read more about Predicting Alzheimer's Disease Using Combined Imaging-Whole Genome SNP Data.PubMed
Prediction of cancer drug sensitivity using high-dimensional omic features. Chen, Ting-Huei, and Wei Sun. "Prediction of cancer drug sensitivity using high-dimensional omic features." Biostatistics 18, no. 1 (2017): 1-14. Read more about Prediction of cancer drug sensitivity using high-dimensional omic features.PubMed
Predictive accuracy of covariates for event times. Chen, Li, D Y. Lin, and Donglin Zeng. "Predictive accuracy of covariates for event times." Biometrika 99, no. 3 (2012): 615-630. Read more about Predictive accuracy of covariates for event times.PubMed
PreMeta: a tool to facilitate meta-analysis of rare-variant associations. Tang, Zheng-Zheng, Paul Bunn, Ran Tao, Zhouwen Liu, and Dan-Yu Lin. "PreMeta: a tool to facilitate meta-analysis of rare-variant associations." BMC Genomics 18, no. 1 (2017): 160. Read more about PreMeta: a tool to facilitate meta-analysis of rare-variant associations.PubMed
PreMeta: Facilitates the Exchange of Information Between Software Packages for Meta-Analysis (C++) Tang, Zheng-Zheng, Paul Bunn, Ran Tao, Z Liu, and Dan-Yu Lin. PreMeta: Facilitates the Exchange of Information Between Software Packages for Meta-Analysis (C++)., 2017. Read more about PreMeta: Facilitates the Exchange of Information Between Software Packages for Meta-Analysis (C++)
Principal Components Adjusted Variable Screening. Liu, Zhongkai, Rui Song, Donglin Zeng, and Jiajia Zhang. "Principal Components Adjusted Variable Screening." Comput Stat Data Anal 110 (2017): 134-144. Read more about Principal Components Adjusted Variable Screening.PubMed
Probability-enhanced sufficient dimension reduction for binary classification. Shin, Seung Jun, Yichao Wu, Hao Helen Zhang, and Yufeng Liu. "Probability-enhanced sufficient dimension reduction for binary classification." Biometrics 70, no. 3 (2014): 546-55. Read more about Probability-enhanced sufficient dimension reduction for binary classification.PubMed
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Prospects and challenges for clinical decision support in the era of big data. Naqa, Issam El, Michael R. Kosorok, Judy Jin, Michelle Mierzwa, and Randall K. Ten Haken. "Prospects and challenges for clinical decision support in the era of big data." JCO Clin Cancer Inform 2 (2018). Read more about Prospects and challenges for clinical decision support in the era of big data.PubMed
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Quantifying the Impact of Non-coding Variants on Transcription Factor-DNA Binding. Zhao, Jingkang, Dongshunyi Li, Jungkyun Seo, Andrew S. Allen, and Raluca Gordân. "Quantifying the Impact of Non-coding Variants on Transcription Factor-DNA Binding." Res Comput Mol Biol 10229 (2017): 336-352. Read more about Quantifying the Impact of Non-coding Variants on Transcription Factor-DNA Binding.PubMed
Quantitative trait analysis in sequencing studies under trait-dependent sampling. Lin, Dan-Yu, Donglin Zeng, and Zheng-Zheng Tang. "Quantitative trait analysis in sequencing studies under trait-dependent sampling." Proc Natl Acad Sci U S A 110, no. 30 (2013): 12247-52. Read more about Quantitative trait analysis in sequencing studies under trait-dependent sampling.PubMed
Racial Differences in Diffusion of Intensity-Modulated Radiation Therapy for Localized Prostate Cancer. Cobran, Ewan K., Ronald C. Chen, Robert Overman, Anne-Marie Meyer, Tzy-Mey Kuo, Jonathon O'Brien, Til Stürmer, Nathan C. Sheets, Gregg H. Goldin, Dolly C. Penn et al. "Racial Differences in Diffusion of Intensity-Modulated Radiation Therapy for Localized Prostate Cancer." Am J Mens Health 10, no. 5 (2016): 399-407. Read more about Racial Differences in Diffusion of Intensity-Modulated Radiation Therapy for Localized Prostate Cancer.PubMed
RAMSVM: Reinforced angle-based multicategory support vector machines (R). Zhang, Chong, Yufeng Liu, and Shannon T. Holloway. RAMSVM: Reinforced angle-based multicategory support vector machines (R).. 2.0 ed., 2016. Read more about RAMSVM: Reinforced angle-based multicategory support vector machines (R).
Random Effects Model for Multiple Pathway Analysis with Applications to Type II Diabetes Microarray Data. Pang, Herbert, Inyoung Kim, and Hongyu Zhao. "Random Effects Model for Multiple Pathway Analysis with Applications to Type II Diabetes Microarray Data." Stat Biosci 7, no. 2 (2015): 167-186. Read more about Random Effects Model for Multiple Pathway Analysis with Applications to Type II Diabetes Microarray Data.PubMed
Rapid and robust resampling-based multiple-testing correction with application in a genome-wide expression quantitative trait loci study. Zhang, Xiang, Shunping Huang, Wei Sun, and Wei Wang. "Rapid and robust resampling-based multiple-testing correction with application in a genome-wide expression quantitative trait loci study." Genetics 190, no. 4 (2012): 1511-20. Read more about Rapid and robust resampling-based multiple-testing correction with application in a genome-wide expression quantitative trait loci study.PubMed
Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level. Jeng, Xinge Jessie, Zhongyin John Daye, Wenbin Lu, and Jung-Ying Tzeng. "Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level." PLoS Comput Biol 12, no. 6 (2016): e1004993. Read more about Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level.PubMed
Recursively Imputed Survival Trees. Zhu, Ruoqing, and Michael R. Kosorok. "Recursively Imputed Survival Trees." J Am Stat Assoc 107, no. 497 (2012): 331-340. Read more about Recursively Imputed Survival Trees.PubMed
Reexamining Dis/Similarity-Based Tests for Rare-Variant Association with Case-Control Samples. Wang, Charlotte, Jung-Ying Tzeng, Pei-Zhen Wu, Martin Preisig, and Chuhsing Kate Hsiao. "Reexamining Dis/Similarity-Based Tests for Rare-Variant Association with Case-Control Samples." Genetics 209, no. 1 (2018): 105-113. Read more about Reexamining Dis/Similarity-Based Tests for Rare-Variant Association with Case-Control Samples.PubMed
Reinforced Angle-based Multicategory Support Vector Machines. Zhang, Chong, Yufeng Liu, Junhui Wang, and Hongtu Zhu. "Reinforced Angle-based Multicategory Support Vector Machines." J Comput Graph Stat 25, no. 3 (2016): 806-825. Read more about Reinforced Angle-based Multicategory Support Vector Machines.PubMed
Reinforcement Learning Trees. Zhu, Ruoqing, Donglin Zeng, and Michael R. Kosorok. "Reinforcement Learning Trees." J Am Stat Assoc 110, no. 512 (2015): 1770-1784. Read more about Reinforcement Learning Trees.PubMed
Rejoinder to "A note on testing and estimation in marker-set association study using semiparametric quantile regression kernel machine". Kong, Dehan, Arnab Maity, Fang-Chi Hsu, and Jung-Ying Tzeng. "Rejoinder to "A note on testing and estimation in marker-set association study using semiparametric quantile regression kernel machine"." Biometrics 74, no. 2 (2018): 767-768. Read more about Rejoinder to "A note on testing and estimation in marker-set association study using semiparametric quantile regression kernel machine".PubMed
Research methods for clinical trials in personalized medicine: A systematic review. Ren, Zheng, Marie Davidian, Stephen L. George, Richard M. Goldberg, Fred A. Wright, Anastasios A. Tsiatis, and Michael R. Kosorok. "Research methods for clinical trials in personalized medicine: A systematic review." In Lost In Translation: Barriers to Incentives for Translational Research in Medical Sciences. Singapore: World Scientific, 2014. Read more about Research methods for clinical trials in personalized medicine: A systematic review.
Residual Weighted Learning for Estimating Individualized Treatment Rules. Zhou, Xin, Nicole Mayer-Hamblett, Umer Khan, and Michael R. Kosorok. "Residual Weighted Learning for Estimating Individualized Treatment Rules." J Am Stat Assoc 112, no. 517 (2017): 169-187. Read more about Residual Weighted Learning for Estimating Individualized Treatment Rules.PubMed
Robust kernel association testing (RobKAT). Martinez, Kara, Arnab Maity, Robert H. Yolken, Patrick F. Sullivan, and Jung-Ying Tzeng. "Robust kernel association testing (RobKAT)." Genet Epidemiol 44, no. 3 (2020): 272-282. Read more about Robust kernel association testing (RobKAT).PubMed
Robust Multicategory Support Vector Machines using Difference Convex Algorithm. Zhang, Chong, Minh Pham, Sheng Fu, and Yufeng Liu. "Robust Multicategory Support Vector Machines using Difference Convex Algorithm." Math Program 169, no. 1 (2018): 277-305. Read more about Robust Multicategory Support Vector Machines using Difference Convex Algorithm.PubMed
Robust Score Tests With Missing Data in Genomics Studies. Wong, Kin Yau, Donglin Zeng, and D Y. Lin. "Robust Score Tests With Missing Data in Genomics Studies." J Am Stat Assoc 114, no. 528 (2019): 1778-1786. Read more about Robust Score Tests With Missing Data in Genomics Studies.PubMed
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RSNPset: Genome-wide SNP set analysis on the basis of efficient scores (R). Yi, Chanhee, Alexander Sibley, and Kouros Owzar. RSNPset: Genome-wide SNP set analysis on the basis of efficient scores (R).. v0.2 ed., 2014. Read more about RSNPset: Genome-wide SNP set analysis on the basis of efficient scores (R).
SAFE-clustering: Single-cell Aggregated (from Ensemble) clustering for single-cell RNA-seq data. Yang, Yuchen, Ruth Huh, Houston W. Culpepper, Yuan Lin, Michael I. Love, and Yun Li. "SAFE-clustering: Single-cell Aggregated (from Ensemble) clustering for single-cell RNA-seq data." Bioinformatics 35, no. 8 (2019): 1269-1277. Read more about SAFE-clustering: Single-cell Aggregated (from Ensemble) clustering for single-cell RNA-seq data.PubMed
SAME: Somatic mutation Association test with Measurement Errors (R) Liu, Yang, Wei Sun, and Qianchuan He. SAME: Somatic mutation Association test with Measurement Errors (R)., 2018. Read more about SAME: Somatic mutation Association test with Measurement Errors (R)
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SCORE-SeqTDS: Score tests for sequencing studies with trait-dependent sampling (C). Lin, Dan-Yu, Donglin Zeng, and Zheng-Zheng Tang. SCORE-SeqTDS: Score tests for sequencing studies with trait-dependent sampling (C).. 3.0 ed., 2013. Read more about SCORE-SeqTDS: Score tests for sequencing studies with trait-dependent sampling (C).
Semiparametric estimation of the accelerated failure time model with partly interval-censored data. Gao, Fei, Donglin Zeng, and Dan-Yu Lin. "Semiparametric estimation of the accelerated failure time model with partly interval-censored data." Biometrics 73, no. 4 (2017): 1161-1168. Read more about Semiparametric estimation of the accelerated failure time model with partly interval-censored data.PubMed
Semiparametric regression analysis of interval-censored competing risks data. Mao, Lu, Dan-Yu Lin, and Donglin Zeng. "Semiparametric regression analysis of interval-censored competing risks data." Biometrics 73, no. 3 (2017): 857-865. Read more about Semiparametric regression analysis of interval-censored competing risks data.PubMed
Semiparametric regression analysis of interval-censored data with informative dropout. Gao, Fei, Donglin Zeng, and Dan-Yu Lin. "Semiparametric regression analysis of interval-censored data with informative dropout." Biometrics 74, no. 4 (2018): 1213-1222. Read more about Semiparametric regression analysis of interval-censored data with informative dropout.PubMed
Semiparametric Regression Analysis of Multiple Right- and Interval-Censored Events. Gao, Fei, Donglin Zeng, David Couper, and D Y. Lin. "Semiparametric Regression Analysis of Multiple Right- and Interval-Censored Events." J Am Stat Assoc 114, no. 527 (2019): 1232-1240. Read more about Semiparametric Regression Analysis of Multiple Right- and Interval-Censored Events.PubMed
Semiparametric regression for the weighted composite endpoint of recurrent and terminal events. Mao, Lu, and D Y. Lin. "Semiparametric regression for the weighted composite endpoint of recurrent and terminal events." Biostatistics 17, no. 2 (2016): 390-403. Read more about Semiparametric regression for the weighted composite endpoint of recurrent and terminal events.PubMed
Semiparametric sieve maximum likelihood estimation under cure model with partly interval censored and left truncated data for application to spontaneous abortion. Wu, Yuan, Christina D. Chambers, and Ronghui Xu. "Semiparametric sieve maximum likelihood estimation under cure model with partly interval censored and left truncated data for application to spontaneous abortion." Lifetime Data Anal 25, no. 3 (2019): 507-528. Read more about Semiparametric sieve maximum likelihood estimation under cure model with partly interval censored and left truncated data for application to spontaneous abortion.PubMed
Semiparametric Single-Index Model for Estimating Optimal Individualized Treatment Strategy. Song, Rui, Shikai Luo, Donglin Zeng, Hao Helen Zhang, Wenbin Lu, and Zhiguo Li. "Semiparametric Single-Index Model for Estimating Optimal Individualized Treatment Strategy." Electron J Stat 11, no. 1 (2017): 364-384. Read more about Semiparametric Single-Index Model for Estimating Optimal Individualized Treatment Strategy.PubMed
SEQGWAS: Integrative analysis of sequencing and GWAS data (C/C++). Hu, Yi-Juan, Yun Li, Paul L. Auer, and Dan-Yu Lin. SEQGWAS: Integrative analysis of sequencing and GWAS data (C/C++).. 1.0 ed., 2015. Read more about SEQGWAS: Integrative analysis of sequencing and GWAS data (C/C++).
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Simultaneous Clustering and Estimation of Heterogeneous Graphical Models. Hao, Botao, Will Wei Sun, Yufeng Liu, and Guang Cheng. "Simultaneous Clustering and Estimation of Heterogeneous Graphical Models." J Mach Learn Res 18 (2018). Read more about Simultaneous Clustering and Estimation of Heterogeneous Graphical Models.PubMed
Simultaneous Critical Values For T-Tests In Very High Dimensions. Cao, Hongyuan, and Michael R. Kosorok. "Simultaneous Critical Values For T-Tests In Very High Dimensions." Bernoulli (Andover) 17, no. 1 (2011): 347-394. Read more about Simultaneous Critical Values For T-Tests In Very High Dimensions.PubMed
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SNPpy--database management for SNP data from genome wide association studies. Mitha, Faheem, Herodotos Herodotou, Nedyalko Borisov, Chen Jiang, Josh Yoder, and Kouros Owzar. "SNPpy--database management for SNP data from genome wide association studies." PLoS One 6, no. 10 (2011): e24982. Read more about SNPpy--database management for SNP data from genome wide association studies.PubMed
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SparkScore: Leveraging Apache Spark for Distributed Genomic Inference. Bahmani, A, Alexander Sibley, M Parsian, Kouros Owzar, and F Mueller. SparkScore: Leveraging Apache Spark for Distributed Genomic Inference. In 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE Computer Society Conference Publishing Services, 2016. Read more about SparkScore: Leveraging Apache Spark for Distributed Genomic Inference.
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Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development. Phanstiel, Douglas H., Kevin Van Bortle, Damek Spacek, Gaelen T. Hess, Muhammad Saad Shamim, Ido Machol, Michael I. Love, Erez Lieberman Aiden, Michael C. Bassik, and Michael P. Snyder. "Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development." Mol Cell 67, no. 6 (2017): 1037-1048.e6. Read more about Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development.PubMed
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Statistical significance for hierarchical clustering. Kimes, Patrick K., Yufeng Liu, David Neil Hayes, and James Stephen Marron. "Statistical significance for hierarchical clustering." Biometrics 73, no. 3 (2017): 811-821. Read more about Statistical significance for hierarchical clustering.PubMed
Statistical Significance of Clustering using Soft Thresholding. Huang, Hanwen, Yufeng Liu, Ming Yuan, and J S. Marron. "Statistical Significance of Clustering using Soft Thresholding." J Comput Graph Stat 24, no. 4 (2015): 975-993. Read more about Statistical Significance of Clustering using Soft Thresholding.PubMed
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SUGEN: Genetic Association Analysis Under Complex Survey Sampling (C++) Lin, Dan-Yu, R Tao, W Kalsbeek, Donglin Zeng, Franklyn Gonzalez, Lindsay Fernández-Rhodes, Mariaelisa Graff, Gary G. Koch, Kari E. North, and Gerardo Heiss. SUGEN: Genetic Association Analysis Under Complex Survey Sampling (C++)., 2014. Read more about SUGEN: Genetic Association Analysis Under Complex Survey Sampling (C++)
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Testing and estimation in marker-set association study using semiparametric quantile regression kernel machine. Kong, Dehan, Arnab Maity, Fang-Chi Hsu, and Jung-Ying Tzeng. "Testing and estimation in marker-set association study using semiparametric quantile regression kernel machine." Biometrics 72, no. 2 (2016): 364-71. Read more about Testing and estimation in marker-set association study using semiparametric quantile regression kernel machine.PubMed
The association between copy number aberration, DNA methylation and gene expression in tumor samples. Sun, Wei, Paul Bunn, Chong Jin, Paul Little, Vasyl Zhabotynsky, Charles M. Perou, David Neil Hayes, Mengjie Chen, and Dan-Yu Lin. "The association between copy number aberration, DNA methylation and gene expression in tumor samples." Nucleic Acids Res 46, no. 6 (2018): 3009-3018. Read more about The association between copy number aberration, DNA methylation and gene expression in tumor samples.PubMed
The Change-Plane Cox Model. Wei, Susan, and Michael R. Kosorok. "The Change-Plane Cox Model." Biometrika 105, no. 4 (2018): 891-903. Read more about The Change-Plane Cox Model.PubMed
THE INTERACTIVE DECISION COMMITTEE FOR CHEMICAL TOXICITY ANALYSIS. Kang, Chaeryon, Hao Zhu, Fred A. Wright, Fei Zou, and Michael R. Kosorok. "THE INTERACTIVE DECISION COMMITTEE FOR CHEMICAL TOXICITY ANALYSIS." J Stat Res 46, no. 2 (2012): 157-186. Read more about THE INTERACTIVE DECISION COMMITTEE FOR CHEMICAL TOXICITY ANALYSIS.PubMed
The optimal power puzzle: scrutiny of the monotone likelihood ratio assumption in multiple testing. Cao, Hongyuan, Wenguang Sun, and Michael R. Kosorok. "The optimal power puzzle: scrutiny of the monotone likelihood ratio assumption in multiple testing." Biometrika 100, no. 2 (2013): 495-502. Read more about The optimal power puzzle: scrutiny of the monotone likelihood ratio assumption in multiple testing.PubMed
Tree based weighted learning for estimating individualized treatment rules with censored data. Cui, Yifan, Ruoqing Zhu, and Michael Kosorok. "Tree based weighted learning for estimating individualized treatment rules with censored data." Electron J Stat 11, no. 2 (2017): 3927-3953. Read more about Tree based weighted learning for estimating individualized treatment rules with censored data.PubMed
TwoPhaseReg: Regression Analysis Under General Two-Phase Sampling (R) Tao, Ran. TwoPhaseReg: Regression Analysis Under General Two-Phase Sampling (R)., 2018. Read more about TwoPhaseReg: Regression Analysis Under General Two-Phase Sampling (R)
Tximeta: Reference sequence checksums for provenance identification in RNA-seq. Love, Michael I., Charlotte Soneson, Peter F. Hickey, Lisa K. Johnson, Tessa N Pierce, Lori Shepherd, Martin Morgan, and Rob Patro. "Tximeta: Reference sequence checksums for provenance identification in RNA-seq." PLoS Comput Biol 16, no. 2 (2020): e1007664. Read more about Tximeta: Reference sequence checksums for provenance identification in RNA-seq.PubMed
Unified Analysis of Secondary Traits in Case-Control Association Studies. Ghosh, Arpita, Fred A. Wright, and Fei Zou. "Unified Analysis of Secondary Traits in Case-Control Association Studies." J Am Stat Assoc 108, no. 502 (2013). Read more about Unified Analysis of Secondary Traits in Case-Control Association Studies.PubMed
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Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma. Jusakul, Apinya, Ioana Cutcutache, Chern Han Yong, Jing Quan Lim, Mi Ni Huang, Nisha Padmanabhan, Vishwa Nellore, Sarinya Kongpetch, Alvin Wei Tian Ng, Ley Moy Ng et al. "Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma." Cancer Discov 7, no. 10 (2017): 1116-1135. Read more about Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma.PubMed