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Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

By E. V. Thomas, K. H. Phillippy, B. Brahamsha, D. M. Haaland, J. A. Timlin, L. D. H. Elbourne, B. Palenik and I. T. Paulsen

Abstract

Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition

Topics: Research Article
Publisher: Hindawi Publishing Corporation
OAI identifier: oai:pubmedcentral.nih.gov:2673484
Provided by: PubMed Central
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    Citations

    1. (1996). A genetic manipulation system for oceanic cyanobacteria of the genus Synechococcus,”
    2. (2003). a z s i ,K .A .K a y ,A . - L .B a r a b ´
    3. (2004). Analysis of variance components in gene expression data,”
    4. (1999). Application of molecular techniques to addressing the role of P as a key effector in marine ecosystems,”
    5. (2001). Assessing gene significance from cDNA microarray expression data via mixed models,”
    6. (2001). Characterization of a two-component signal transduction system involved in the induction of alkaline phosphatase under phosphate-limiting conditions in Synechocystis sp.
    7. (2006). Computational inference and experimental validation of the nitrogen assimilation regulatory network in cyanobacterium Synechococcus sp.
    8. (2003). Data Analysis Tools for DNA Microarrays, Chapman & Hall/CRC,
    9. (2004). Exploration and Analysis of DNA Microarray and Protein Array Data,J o h nW i l e y&S o n s ,
    10. (2004). Identification of competence pheromone responsive genes in Streptococcus pneumoniae by use of
    11. (2000). Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations,”
    12. (2005). S c h a u p p ,G .J i a n g ,T .G .M y e r s ,a n dM .A .W i l s o n , “Active mixing during hybridization improves the accuracy and reproducibility of microarray results,”
    13. (1989). S t o c k ,A .J .N i n f a ,a n dA .M .S t o c k ,“ P r o t e i np h o s p h o -rylation and regulation of adaptive responses in bacteria,”
    14. (2001). Significance analysis of microarrays applied to the ionizing radiation response,”
    15. (2002). Statistical analysis of a gene expression microarray experiment with replication,”
    16. (2001). Statistical design and the analysis of gene expression microarray data,”
    17. (2003). Statistical tests for differential expression in cDNA microarray experiments,”
    18. (2003). The genome of a motile marine
    19. (2003). TM4: a free, opensource system for microarray data management and analysis,”
    20. (1992). Variance Components,

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