Literature DB >> 11355567

Statistical design and the analysis of gene expression microarray data.

M K Kerr1, G A Churchill.   

Abstract

Gene expression microarrays are an innovative technology with enormous promise to help geneticists explore and understand the genome. Although the potential of this technology has been clearly demonstrated, many important and interesting statistical questions persist. We relate certain features of microarrays to other kinds of experimental data and argue that classical statistical techniques are appropriate and useful. We advocate greater attention to experimental design issues and a more prominent role for the ideas of statistical inference in microarray studies.

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Year:  2001        PMID: 11355567     DOI: 10.1017/s0016672301005055

Source DB:  PubMed          Journal:  Genet Res        ISSN: 0016-6723            Impact factor:   1.588


  144 in total

Review 1.  Microarray data quality analysis: lessons from the AFGC project. Arabidopsis Functional Genomics Consortium.

Authors:  David Finkelstein; Rob Ewing; Jeremy Gollub; Fredrik Sterky; J Michael Cherry; Shauna Somerville
Journal:  Plant Mol Biol       Date:  2002-01       Impact factor: 4.076

Review 2.  A strategy for identifying osteoporosis risk genes.

Authors:  David Rowe; Alexander Lichtler
Journal:  Endocrine       Date:  2002-02       Impact factor: 3.633

3.  Monitoring global messenger RNA changes in externally controlled microarray experiments.

Authors:  Jeroen van de Peppel; Patrick Kemmeren; Harm van Bakel; Marijana Radonjic; Dik van Leenen; Frank C P Holstege
Journal:  EMBO Rep       Date:  2003-04       Impact factor: 8.807

4.  Combining mapping and arraying: An approach to candidate gene identification.

Authors:  M L Wayne; L M McIntyre
Journal:  Proc Natl Acad Sci U S A       Date:  2002-11-01       Impact factor: 11.205

5.  Expression profiling with oligonucleotide arrays: technologies and applications for neurobiology.

Authors:  Timothy J Sendera; David Dorris; Ramesh Ramakrishnan; Allen Nguyen; Dionisios Trakas; Abhijit Mazumder
Journal:  Neurochem Res       Date:  2002-10       Impact factor: 3.996

6.  Statistical analysis of multiplex brain gene expression images.

Authors:  Alex Ossadtchi; Vanessa M Brown; Arshad H Khan; Simon R Cherry; Thomas E Nichols; Richard M Leahy; Desmond J Smith
Journal:  Neurochem Res       Date:  2002-10       Impact factor: 3.996

7.  Pheromone-mediated gene expression in the honey bee brain.

Authors:  Christina M Grozinger; Noura M Sharabash; Charles W Whitfield; Gene E Robinson
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-22       Impact factor: 11.205

8.  Photosynthetic acclimation is reflected in specific patterns of gene expression in drought-stressed loblolly pine.

Authors:  Jonathan I Watkinson; Allan A Sioson; Cecilia Vasquez-Robinet; Maulik Shukla; Deept Kumar; Margaret Ellis; Lenwood S Heath; Naren Ramakrishnan; Boris Chevone; Layne T Watson; Leonel van Zyl; Ulrika Egertsdotter; Ronald R Sederoff; Ruth Grene
Journal:  Plant Physiol       Date:  2003-12       Impact factor: 8.340

9.  A novel mechanism of alternative promoter and splicing regulates the epitope generation of tumor antigen CML66-L.

Authors:  Yan Yan; Leuyen Phan; Fan Yang; Moshe Talpaz; Yu Yang; Zeyu Xiong; Bernard Ng; Nikolai A Timchenko; Catherine J Wu; Jerome Ritz; Hong Wang; Xiao-Feng Yang
Journal:  J Immunol       Date:  2004-01-01       Impact factor: 5.422

10.  Gene expression profiling of the hypoxia signaling pathway in hypoxia-inducible factor 1alpha null mouse embryonic fibroblasts.

Authors:  Ajith Vengellur; Barbara G Woods; Heather E Ryan; Randall S Johnson; John J LaPres
Journal:  Gene Expr       Date:  2003
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