IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v47y2004i3p611-637.html

On estimating the proportion of true null hypotheses for false discovery rate controlling procedures in exploratory DNA microarray studies

Author

Listed:
  • Nguyen, Danh V.

Abstract

No abstract is available for this item.

Suggested Citation

  • Nguyen, Danh V., 2004. "On estimating the proportion of true null hypotheses for false discovery rate controlling procedures in exploratory DNA microarray studies," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 611-637, October.
    • Handle: RePEc:eee:csdana:v:47:y:2004:i:3:p:611-637
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(04)00004-0
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Allison, David B. & Gadbury, Gary L. & Heo, Moonseong & Fernandez, Jose R. & Lee, Cheol-Koo & Prolla, Tomas A. & Weindruch, Richard, 2002. "A mixture model approach for the analysis of microarray gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 1-20, March.
    2. Nguyen, Danh V. & Rocke, D.M.David M., 2004. "On partial least squares dimension reduction for microarray-based classification: a simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 46(3), pages 407-425, June.
    3. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. de Uña-Alvarez Jacobo, 2011. "On the Statistical Properties of SGoF Multitesting Method," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-30, April.
    2. Friguet, Chloé & Causeur, David, 2011. "Estimation of the proportion of true null hypotheses in high-dimensional data under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2665-2676, September.
    3. de Uña-Alvarez Jacobo, 2012. "The Beta-Binomial SGoF method for multiple dependent tests," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-32, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hunt, Daniel L. & Cheng, Cheng & Pounds, Stanley, 2009. "The beta-binomial distribution for estimating the number of false rejections in microarray gene expression studies," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1688-1700, March.
    2. Andrew Y. Chen, 2022. "Do t-Statistic Hurdles Need to be Raised?," Papers 2204.10275, arXiv.org, revised Apr 2024.
    3. Park, DoHwan & Park, Junyong & Zhong, Xiaosong & Sadelain, Michel, 2011. "Estimation of empirical null using a mixture of normals and its use in local false discovery rate," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2421-2432, July.
    4. Cheng, Cheng, 2009. "Internal validation inferences of significant genomic features in genome-wide screening," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 788-800, January.
    5. Robert R. Delongchamp & John F. Bowyer & James J. Chen & Ralph L. Kodell, 2004. "Multiple-Testing Strategy for Analyzing cDNA Array Data on Gene Expression," Biometrics, The International Biometric Society, vol. 60(3), pages 774-782, September.
    6. Xiang, Qinfang & Edwards, Jode & Gadbury, Gary L., 2006. "Interval estimation in a finite mixture model: Modeling P-values in multiple testing applications," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 570-586, November.
    7. Ferreira, J.A. & Nyangoma, S.O., 2008. "A multivariate version of the Benjamini-Hochberg method," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 2108-2124, October.
    8. Shigeyuki Matsui & Shu Zeng & Takeharu Yamanaka & John Shaughnessy, 2008. "Sample Size Calculations Based on Ranking and Selection in Microarray Experiments," Biometrics, The International Biometric Society, vol. 64(1), pages 217-226, March.
    9. Yongqiang Tang & Subhashis Ghosal & Anindya Roy, 2007. "Nonparametric Bayesian Estimation of Positive False Discovery Rates," Biometrics, The International Biometric Society, vol. 63(4), pages 1126-1134, December.
    10. Miecznikowski, Jeffrey C. & Gold, David & Shepherd, Lori & Liu, Song, 2011. "Deriving and comparing the distribution for the number of false positives in single step methods to control k-FWER," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1695-1705, November.
    11. Youngchao Ge & Sandrine Dudoit & Terence Speed, 2003. "Resampling-based multiple testing for microarray data analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 1-77, June.
    12. Kondylis, Athanassios & Whittaker, Joe, 2008. "Spectral preconditioning of Krylov spaces: Combining PLS and PC regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2588-2603, January.
    13. Timothy B. Armstrong & Michal Kolesár & Mikkel Plagborg‐Møller, 2022. "Robust Empirical Bayes Confidence Intervals," Econometrica, Econometric Society, vol. 90(6), pages 2567-2602, November.
    14. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    15. Parrish, Rudolph S. & Spencer III, Horace J. & Xu, Ping, 2009. "Distribution modeling and simulation of gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1650-1660, March.
    16. Bethany L Dearlove & Simon D W Frost, 2015. "Measuring Asymmetry in Time-Stamped Phylogenies," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-16, July.
    17. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    18. Dørum Guro & Snipen Lars & Solheim Margrete & Saebo Solve, 2011. "Smoothing Gene Expression Data with Network Information Improves Consistency of Regulated Genes," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-26, August.
    19. Bourdeau-Brien, Michael & Kryzanowski, Lawrence, 2017. "The impact of natural disasters on the stock returns and volatilities of local firms," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 259-270.
    20. Fernando A. Quintana & Peter Müller & Gary L. Rosner & Mary V. Relling, 2008. "A semiparametric Bayesian model for repeatedly repeated binary outcomes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(4), pages 419-431, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:47:y:2004:i:3:p:611-637. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.