Pathway Analysis of Expression Data: Deciphering Functional Building Blocks of Complex Diseases
Author
Abstract
Suggested Citation
DOI: 10.1371/journal.pcbi.1002053
Download full text from publisher
References listed on IDEAS
- Qiu Xing & Klebanov Lev & Yakovlev Andrei, 2005. "Correlation Between Gene Expression Levels and Limitations of the Empirical Bayes Methodology for Finding Differentially Expressed Genes," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-32, November.
- Eric E. Schadt, 2009. "Molecular networks as sensors and drivers of common human diseases," Nature, Nature, vol. 461(7261), pages 218-223, September.
- van der Laan Mark J. & Dudoit Sandrine & Pollard Katherine S., 2004. "Augmentation Procedures for Control of the Generalized Family-Wise Error Rate and Tail Probabilities for the Proportion of False Positives," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-27, June.
- Mark van der Laan & Sandrine Dudoit & Katherine Pollard, 2004. "Multiple Testing. Part III. Procedures for Control of the Generalized Family-Wise Error Rate and Proportion of False Positives," U.C. Berkeley Division of Biostatistics Working Paper Series 1140, Berkeley Electronic Press.
- Efron B. & Tibshirani R. & Storey J.D. & Tusher V., 2001. "Empirical Bayes Analysis of a Microarray Experiment," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1151-1160, December.
- Shojaie Ali & Michailidis George, 2010. "Network Enrichment Analysis in Complex Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-36, May.
- Mark Reimers, 2010. "Making Informed Choices about Microarray Data Analysis," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-7, May.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Alin Tomoiaga & Peter Westfall & Michele Donato & Sorin Draghici & Sonia Hassan & Roberto Romero & Paola Tellaroli, 2016. "Pathway crosstalk effects: shrinkage and disentanglement using a Bayesian hierarchical model," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 374-394, October.
- Ryu Duchwan & Xu Hongyan & George Varghese & Su Shaoyong & Wang Xiaoling & Shi Huidong & Podolsky Robert H., 2016. "Differential methylation tests of regulatory regions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(3), pages 237-251, June.
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.- Guo Wenge & Peddada Shyamal, 2008. "Adaptive Choice of the Number of Bootstrap Samples in Large Scale Multiple Testing," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-21, March.
- Pallavi Basu & Luella Fu & Alessio Saretto & Wenguang Sun, 2021. "Empirical Bayes Control of the False Discovery Exceedance," Working Papers 2115, Federal Reserve Bank of Dallas.
- van der Laan Mark J. & Hubbard Alan E., 2006. "Quantile-Function Based Null Distribution in Resampling Based Multiple Testing," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 5(1), pages 1-30, May.
- Montazeri Zahra & Yanofsky Corey M. & Bickel David R., 2010. "Shrinkage Estimation of Effect Sizes as an Alternative to Hypothesis Testing Followed by Estimation in High-Dimensional Biology: Applications to Differential Gene Expression," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-33, June.
- Djalel-Eddine Meskaldji & Dimitri Van De Ville & Jean-Philippe Thiran & Stephan Morgenthaler, 2020. "A comprehensive error rate for multiple testing," Statistical Papers, Springer, vol. 61(5), pages 1859-1874, October.
- G�nther Fink & Margaret McConnell & Sebastian Vollmer, 2014.
"Testing for heterogeneous treatment effects in experimental data: false discovery risks and correction procedures,"
Journal of Development Effectiveness, Taylor & Francis Journals, vol. 6(1), pages 44-57, January.
- Fink, Günther & McConnell, Margaret & Vollmer, Sebastian, 2011. "Testing for Heterogeneous Treatment Effects in Experimental Data: False Discovery Risks and Correction Procedures," Hannover Economic Papers (HEP) dp-477, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- Irene Castro-Conde & Jacobo Uña-Álvarez, 2015. "Power, FDR and conservativeness of BB-SGoF method," Computational Statistics, Springer, vol. 30(4), pages 1143-1161, December.
- Christina C. Bartenschlager & Michael Krapp, 2015. "Theorie und Methoden multipler statistischer Vergleiche," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 9(2), pages 107-129, November.
- Gordon, Alexander & Chen, Linlin & Glazko, Galina & Yakovlev, Andrei, 2009. "Balancing type one and two errors in multiple testing for differential expression of genes," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1622-1629, March.
- Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2010.
"Hypothesis Testing in Econometrics,"
Annual Review of Economics, Annual Reviews, vol. 2(1), pages 75-104, September.
- Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2009. "Hypothesis testing in econometrics," IEW - Working Papers 444, Institute for Empirical Research in Economics - University of Zurich.
- Merrill Birkner & Sandra Sinisi & Mark van der Laan, 2004. "Multiple Testing and Data Adaptive Regression: An Application to HIV-1 Sequence Data," U.C. Berkeley Division of Biostatistics Working Paper Series 1161, Berkeley Electronic Press.
- Bickel David R., 2012. "Empirical Bayes Interval Estimates that are Conditionally Equal to Unadjusted Confidence Intervals or to Default Prior Credibility Intervals," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-34, February.
- Mathur, Maya B & VanderWeele, Tyler J., 2018. "Statistical methods for evidence synthesis," Thesis Commons kd6ja_v1, Center for Open Science.
- Sairam Rayaprolu & Zhiyi Chi, 2021. "False Discovery Variance Reduction in Large Scale Simultaneous Hypothesis Tests," Methodology and Computing in Applied Probability, Springer, vol. 23(3), pages 711-733, September.
- Mathur, Maya B & VanderWeele, Tyler, 2018. "Statistical methods for evidence synthesis," Thesis Commons kd6ja, Center for Open Science.
- Cerioli, Andrea & Farcomeni, Alessio, 2011. "Error rates for multivariate outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 544-553, January.
- 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.
- Alessio Farcomeni, 2009. "Generalized Augmentation to Control the False Discovery Exceedance in Multiple Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 501-517, September.
- 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.
- Joseph Romano & Azeem Shaikh & Michael Wolf, 2008.
"Control of the false discovery rate under dependence using the bootstrap and subsampling,"
TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 417-442, November.
- Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2008. "Control of the False Discovery Rate under Dependence using the Bootstrap and Subsampling," IEW - Working Papers 337, Institute for Empirical Research in Economics - University of Zurich.
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:plo:pcbi00:1002053. 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: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.