Genome microarray experiments

Manduchi, E., Scearce, M., Brestelli, J.E., Grant, G.R., Kaestner, K.H., and Stoeckert, C.J. (2002) Comparison of different labeling methods for two-channel high-density microarray experiments. Physiol. Genom. 10, 169-179. 

The growing commercial availability and relative affordability of cDNA microarrays combined with well-defined protocols for hybridization has made functional genomics a reality for many laboratories. However microarray experiments produce massive quantities of gene expression and functional genomics data, the analysis of which is complicated and involves many steps, each requiring careful consideration. 

Pan W, Lin J, Le G. 2002. How many replicates of arrays are required to detect gene expression changes in microarray experiments A mixture model approach. Genome Biology 3(5) research0022.1. 

Cui, X. and Churchill, G.A. (2003) Statistical tests for differential expression in cDNA microarray experiments. Genome Biology, 4, 210. 

It stores raw and normalized data from microarray experiments, as well as corresponding image files. In addition, Stanford Microarray Database (SMD) provides interfaces for data retrieval, analysis, and visualization. Access to non-public data is limited to registered Stanford researchers and their collaborators. The site also provides links to other microarray resources (http //genome-www5.stanford.edu/resources.html)... 

The MIAME standard defines the minimum information investigators must report for a microarray experiment to be reproduced. The MAGE standard was born partially from MIAME, and the European Bioinformatics Institute used MIAME and MAGE to guide the development of ArrayEx-press, their public genomic data repository (34). Sample annotation lies at the heart of MIAME, underscoring the need to understand as completely as possible the experimental conditions that may influence the microarray data. Many journals that publish microarray data require the submission of MIAME-supportive microarray data to a public genomic data repository as a condition of publication. These typically include submission of protocols species, strains, and sex used for in vivo studies cell line name and culture conditions for in vitro studies, and other relevant information. 

Each of the tools and databases discussed previously is grounded in a significant amount of both technical and theoretical detail. To illustrate the utility of these tools, practical data-analysis examples are provided that outline how a microarray experiment can be designed and analyzed. In addition, the annotation of an uncharacterized EST is defined and mapped to the genome. These examples also demonstrate how to assign annotation to microarray analysis, when the identify of a EST represented on an array may be unknown. 

Workman C, Jensen LJ, Jarmer H, Berka R, Gautier L, Nielser HB, Saxild HH, Nielsen C, Brunak S, Knudsen S, A new nonlinear normalization method for reducing variability in DNA microarray experiments, Genome Biol., 3 research 0048, 2002. 

Microarray experiments may be observational studies whose sole purpose is to screen the genome for differential gene expressions or they may have more specific aims such as the following. 

The MIAME standard was created by the Functional Genomics Data Society, formerly known as the Microarray Gene Expression Data Society (http // www.mged.org), as an effort to provide standards to specify all the information necessary to describe and interpret unambiguously the results of a microarray experiment (74). The standard defines the contents required for compliance reports but it does not specify the format in which this data should be presented. As a consequence there are a number of different file formats for representing this data, and each public and subscription database has adopted its own format. 

Lian, Y. and Kelemen, A. 2006. Associating phenotypes with molecular events Recent statistical advances and challenges underpinning microarray experiments. Fund. Integr. Genomics f>, 1-13. 

C. Perou, D. Botstein, J. Braman, Universal reference RNA as a standard for microarray experiments, BMC Genomics 2004, 5, 20. 

Forster T, Costa Y, Roy D, et al. (2004). Triple-target microarray experiments a novel experimental strategy. BMC Genomics. 5 13. 

For a gene to form a protein, its DNA has to be converted into RNA, which acts within a ribosome. Various studies have shown that the amount of RNA can vary, indicating functional variation of the gene, quantified in terms of gene expression (51). Microarray experiments represent a genomic technique that has yielded expression information of thousands of genes. 

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