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There are 14266 results for: content related to: Adjusting Batch Effects in Microarray Experiments with Small Sample Size Using Empirical Bayes Methods

  1. Identical Reference Samples and Empirical Bayes Method for Cross-Batch Gene Expression Analysis

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Wynn L Walker, Frank R Sharp, Pages: 131–140, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch11

  2. Batches and Blocks, Sample Pools and Subsamples in the Design and Analysis of Gene Expression Studies

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Andreas Scherer, Pages: 33–50, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch4

  3. Inference with transposable data: modelling the effects of row and column correlations

    Journal of the Royal Statistical Society: Series B (Statistical Methodology)

    Volume 74, Issue 4, September 2012, Pages: 721–743, Genevera I. Allen and Robert Tibshirani

    Version of Record online : 16 MAR 2012, DOI: 10.1111/j.1467-9868.2011.01027.x

  4. Aspects of Technical Bias

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Martin Schumacher, Frank Staedtler, Wendell D Jones, Andreas Scherer, Pages: 51–60, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch5

  5. Microarray Gene Expression: The Effects of Varying Certain Measurement Conditions

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Walter Liggett, Jean Lozach, Anne Bergstrom Lucas, Ron L Peterson, Marc L Salit, Danielle Thierry-Mieg, Jean Thierry-Mieg, Russell D Wolfinger, Pages: 101–111, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch9

  6. Covariance adjustment for batch effect in gene expression data

    Statistics in Medicine

    Volume 33, Issue 15, 10 July 2014, Pages: 2681–2695, Jung Ae Lee, Kevin K. Dobbin and Jeongyoun Ahn

    Version of Record online : 28 MAR 2014, DOI: 10.1002/sim.6157

  7. Batch Profile Estimation, Correction, and Scoring

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Tzu-Ming Chu, Wenjun Bao, Russell S Thomas, Russell D Wolfinger, Pages: 155–165, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch13

  8. You have free access to this content
    Front Matter

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Andreas Scherer, Pages: i–xx, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.fmatter

  9. Principal Variance Components Analysis: Estimating Batch Effects in Microarray Gene Expression Data

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Jianying Li, Pierre R Bushel, Tzu-Ming Chu, Russell D Wolfinger, Pages: 141–154, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch12

  10. Potential Sources of Spurious Associations and Batch Effects in Genome-Wide Association Studies

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Huixiao Hong, Leming Shi, James C Fuscoe, Federico Goodsaid, Donna Mendrick, Weida Tong, Pages: 191–201, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch16

  11. Biomarker discovery study design for type 1 diabetes in The Environmental Determinants of Diabetes in the Young (TEDDY) study

    Diabetes/Metabolism Research and Reviews

    Volume 30, Issue 5, July 2014, Pages: 424–434, Hye-Seung Lee, Brant R. Burkhardt, Wendy McLeod, Susan Smith, Chris Eberhard, Kristian Lynch, David Hadley, Marian Rewers, Olli Simell, Jin-Xiong She, Bill Hagopian, Ake Lernmark, Beena Akolkar, Anette G. Ziegler, Jeffrey P. Krischer and The TEDDY study group

    Version of Record online : 2 JUL 2014, DOI: 10.1002/dmrr.2510

  12. Class-paired Fuzzy SubNETs: A paired variant of the rank-based network analysis family for feature selection based on protein complexes

    PROTEOMICS

    Volume 17, Issue 10, May 2017, Wilson Wen Bin Goh and Limsoon Wong

    Version of Record online : 18 MAY 2017, DOI: 10.1002/pmic.201700093

  13. Variation, Variability, Batches and Bias in Microarray Experiments: An Introduction

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Andreas Scherer, Pages: 1–4, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch1

  14. Experimental Design

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Andreas Scherer, Pages: 19–31, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch3

  15. How to Deal with Batch Effect in Sequential Microarray Experiments?

    Molecular Informatics

    Volume 29, Issue 5, May 17, 2010, Pages: 387–393, Nino Demetrashvili , Ken Kron , Vaijayanti Pethe , Bharati Bapat  and Laurent Briollais 

    Version of Record online : 14 MAY 2010, DOI: 10.1002/minf.200900019

  16. Batch Effect Estimation of Microarray Platforms with Analysis of Variance

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Nysia I George, James J Chen, Pages: 75–85, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch7

  17. Pitfalls of merging GWAS data: lessons learned in the eMERGE network and quality control procedures to maintain high data quality

    Genetic Epidemiology

    Volume 35, Issue 8, December 2011, Pages: 887–898, Rebecca L. Zuvich, Loren L. Armstrong, Suzette J. Bielinski, Yuki Bradford, Christopher S. Carlson, Dana C. Crawford, Andrew T. Crenshaw, Mariza de Andrade, Kimberly F. Doheny, Jonathan L. Haines, M. Geoffrey Hayes, Gail P. Jarvik, Lan Jiang, Iftikhar J. Kullo, Rongling Li, Hua Ling, Teri A. Manolio, Martha E. Matsumoto, Catherine A. McCarty, Andrew N. McDavid, Daniel B. Mirel, Lana M. Olson, Justin E. Paschall, Elizabeth W. Pugh, Luke V. Rasmussen, Laura J. Rasmussen-Torvik, Stephen D. Turner, Russell A. Wilke and Marylyn D. Ritchie

    Version of Record online : 28 NOV 2011, DOI: 10.1002/gepi.20639

  18. You have free access to this content
    Genetics of gene expression characterizes response to selective breeding for alcohol preference

    Genes, Brain and Behavior

    Volume 13, Issue 8, November 2014, Pages: 743–757, P. L. Hoffman, L. M. Saba, S. Flink, N. J. Grahame, K. Kechris and B. Tabakoff

    Version of Record online : 29 SEP 2014, DOI: 10.1111/gbb.12175

  19. You have free access to this content
    References

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Andreas Scherer, Pages: 231–243, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.refs

  20. Microarray Platforms and Aspects of Experimental Variation

    Batch Effects and Noise in Microarray Experiments: Sources and Solutions

    Andreas Scherer, Pages: 5–17, 2009

    Published Online : 2 NOV 2009, DOI: 10.1002/9780470685983.ch2