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Detecting Differential Expressions in GeneChip Microarray Studies: A Quantile Approach

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  • Wang, Huixia
  • He, Xuming

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  • Wang, Huixia & He, Xuming, 2007. "Detecting Differential Expressions in GeneChip Microarray Studies: A Quantile Approach," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 104-112, March.
    • Handle: RePEc:bes:jnlasa:v:102:y:2007:p:104-112
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    Cited by:

    1. Sungwan Bang & Soo-Heang Eo & Yong Mee Cho & Myoungshic Jhun & HyungJun Cho, 2016. "Non-crossing weighted kernel quantile regression with right censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(1), pages 100-121, January.
    2. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    3. Liwen Zhang & Huixia Judy Wang & Zhongyi Zhu, 2017. "Composite change point estimation for bent line quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 145-168, February.
    4. Chen, Zhao & Cheng, Vivian Xinyi & Liu, Xu, 2024. "Hypothesis testing on high dimensional quantile regression," Journal of Econometrics, Elsevier, vol. 238(1).
    5. Chi-Chuan Yang & Yi-Hau Chen & Hsing-Yi Chang, 2017. "Joint regression analysis of marginal quantile and quantile association: application to longitudinal body mass index in adolescents," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(5), pages 1075-1090, November.
    6. Huixia Wang & Xuming He, 2008. "An Enhanced Quantile Approach for Assessing Differential Gene Expressions," Biometrics, The International Biometric Society, vol. 64(2), pages 449-457, June.
    7. Galina Besstremyannaya & Sergei Golovan, 2023. "Measuring heterogeneity in hospital productivity: a quantile regression approach," Journal of Productivity Analysis, Springer, vol. 59(1), pages 15-43, February.
    8. Besstremyannaya, Galina, 2017. "Heterogeneous effect of the global financial crisis and the Great East Japan Earthquake on costs of Japanese banks," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 66-89.
    9. Xiaoming Lu & Zhaozhi Fan, 2015. "Weighted quantile regression for longitudinal data," Computational Statistics, Springer, vol. 30(2), pages 569-592, June.
    10. Huixia Judy Wang & Jianhua Hu, 2011. "Identification of Differential Aberrations in Multiple-Sample Array CGH Studies," Biometrics, The International Biometric Society, vol. 67(2), pages 353-362, June.
    11. Antonio F. Galvao & Gabriel Montes-Rojas, 2015. "On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study," Econometrics, MDPI, vol. 3(3), pages 1-13, September.
    12. Andreas Hagemann, 2017. "Cluster-Robust Bootstrap Inference in Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 446-456, January.
    13. Vinciotti Veronica & Yu Keming, 2009. "M-quantile Regression Analysis of Temporal Gene Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-22, September.
    14. Qifa Xu & Chao Cai & Cuixia Jiang & Fang Sun & Xue Huang, 2020. "Block average quantile regression for massive dataset," Statistical Papers, Springer, vol. 61(1), pages 141-165, February.
    15. Bang, Sungwan & Jhun, Myoungshic, 2012. "Simultaneous estimation and factor selection in quantile regression via adaptive sup-norm regularization," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 813-826.
    16. Chen, Zhao & Cheng, Vivian Xinyi & Liu, Xu, 2024. "Reprint: Hypothesis testing on high dimensional quantile regression," Journal of Econometrics, Elsevier, vol. 239(2).
    17. Jianqing Fan & Lingzhou Xue & Hui Zou, 2016. "Multitask Quantile Regression Under the Transnormal Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1726-1735, October.
    18. Alexander Aue & Rex C. Y. Cheung & Thomas C. M. Lee & Ming Zhong, 2014. "Segmented Model Selection in Quantile Regression Using the Minimum Description Length Principle," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1241-1256, September.
    19. Galina Besstremyannaya, 2015. "The adverse effects of incentives regulation in health care: a comparative analysis with the U.S. and Japanese hospital data," Working Papers w0218, Center for Economic and Financial Research (CEFIR).
    20. Galina Besstremyannaya, 2015. "The adverse effects of incentives regulation in health care: a comparative analysis with the U.S. and Japanese hospital data," Working Papers w0218, New Economic School (NES).
    21. Andreas Hagemann, 2023. "Inference on quantile processes with a finite number of clusters," Papers 2301.04687, arXiv.org, revised Jun 2023.

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