Abstract
Genetic variation and SNP analysis starts with generation of sequence-specific signal, followed by the collection of that signal. The final step is extensive data analysis, which starts with conversion of quantifiable raw data and ends up with identified SNPs, frequencies, and sometimes tissue-specific expression patterns (levels). In this chapter we describe and compare the mechanisms of signal generation of several representative SNP analysis platforms. DNA microarray no doubt has its advantage in applications involving the classification and identification of tumor classes, gene discovery, drug dependent transcription mechanisms, as well as prediction of drug response. PCR, xMAP, invader assay, mass spectrometry, and pyrosequencing, on the other hand, are alternative methods of genotyping employed following the large scale screening and discovery of genetic variations. In addition, they offer higher specificity and sensitivity in analysis of both genomic DNA, as well as RNA. By exploiting these technologies, correlative study of the effects of putative genetic variations on cells, tissue-specific and developmentally specific expression is possible. Of extreme value are the many forms of Mass Spectrometry in the areas of sensitive, early cancer diagnosis. Finally, microarray and xMAP are suitable for protein analysis. While protein array offers higher throughput, xMAP is more amendable to the native 3D structure of protein molecules.
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© 2007 Landes Bioscience and Springer Science+Business Media
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Wang, L., Luhm, R., Lei, M. (2007). SNP and Mutation Analysis. In: Mocellin, S. (eds) Microarray Technology and Cancer Gene Profiling. Advances in Experimental Medicine and Biology, vol 593. Springer, New York, NY. https://doi.org/10.1007/978-0-387-39978-2_11
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DOI: https://doi.org/10.1007/978-0-387-39978-2_11
Publisher Name: Springer, New York, NY
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