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Items: 1 to 20 of 129

1.

Generalized shrinkage F-like statistics for testing an interaction term in gene expression analysis in the presence of heteroscedasticity.

Yang J, Casella G, McIntyre LM.

BMC Bioinformatics. 2011 Nov 1;12:427. doi: 10.1186/1471-2105-12-427.

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To permute or not to permute.

Huang Y, Xu H, Calian V, Hsu JC.

Bioinformatics. 2006 Sep 15;22(18):2244-8. Epub 2006 Jul 26.

PMID:
16870938
5.

Improved statistical tests for differential gene expression by shrinking variance components estimates.

Cui X, Hwang JT, Qiu J, Blades NJ, Churchill GA.

Biostatistics. 2005 Jan;6(1):59-75.

PMID:
15618528
6.

Estimating p-values in small microarray experiments.

Yang H, Churchill G.

Bioinformatics. 2007 Jan 1;23(1):38-43. Epub 2006 Oct 30.

PMID:
17077100
7.

Permutation and parametric bootstrap tests for gene-gene and gene-environment interactions.

Bůžková P, Lumley T, Rice K.

Ann Hum Genet. 2011 Jan;75(1):36-45. doi: 10.1111/j.1469-1809.2010.00572.x.

8.

Two-part permutation tests for DNA methylation and microarray data.

Neuhäuser M, Boes T, Jöckel KH.

BMC Bioinformatics. 2005 Feb 22;6:35.

9.

Properties of permutation-based gene tests and controlling type 1 error using a summary statistic based gene test.

Swanson DM, Blacker D, Alchawa T, Ludwig KU, Mangold E, Lange C.

BMC Genet. 2013 Nov 7;14:108. doi: 10.1186/1471-2156-14-108.

10.

Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: applications to differential gene expression.

Montazeri Z, Yanofsky CM, Bickel DR.

Stat Appl Genet Mol Biol. 2010;9:Article23. doi: 10.2202/1544-6115.1504. Epub 2010 Jun 8.

PMID:
20597849
11.

Applying shrinkage variance estimators to the TOST test in high dimensional settings.

Qiu J, Qi Y, Cui X.

Stat Appl Genet Mol Biol. 2014 Jun;13(3):323-41. doi: 10.1515/sagmb-2013-0045.

PMID:
24864302
12.

Moment based gene set tests.

Larson JL, Owen AB.

BMC Bioinformatics. 2015 Apr 28;16:132. doi: 10.1186/s12859-015-0571-7.

13.

Microarray data analysis: a hierarchical T-test to handle heteroscedasticity.

de Menezes RX, Boer JM, van Houwelingen HC.

Appl Bioinformatics. 2004;3(4):229-35.

PMID:
15702953
14.

Variance component score test for time-course gene set analysis of longitudinal RNA-seq data.

Agniel D, Hejblum BP.

Biostatistics. 2017 Mar 10. doi: 10.1093/biostatistics/kxx005. [Epub ahead of print]

PMID:
28334305
15.

Rank-based permutation approaches for non-parametric factorial designs.

Umlauft M, Konietschke F, Pauly M.

Br J Math Stat Psychol. 2017 Mar 15. doi: 10.1111/bmsp.12089. [Epub ahead of print]

PMID:
28295183
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A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data.

Xie Y, Pan W, Khodursky AB.

Bioinformatics. 2005 Dec 1;21(23):4280-8. Epub 2005 Sep 27.

PMID:
16188930
19.

Nonparametric methods for microarray data based on exchangeability and borrowed power.

Lee ML, Whitmore GA, Björkbacka H, Freeman MW.

J Biopharm Stat. 2005;15(5):783-97.

PMID:
16078385
20.

High resolution T association tests of complex diseases based on family data.

Fan R, Knapp M, Wjst M, Zhao C, Xiong M.

Ann Hum Genet. 2005 Mar;69(Pt 2):187-208.

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