Conclusions
Defined broadly, pre-processing involves many potential steps that are essential for successful microarray experimentation. The need for some steps (e.g., experimental design, image analysis) is unquestionable. Other steps are less dogmatic. Data transformation, inspection, and filtering should occur based on individual analytical goals and data management systems. These steps may take on new meaning as different techniques for analysis become widely accepted. A complete and perfect recipe for pre-processing and analyzing microarray experiments does not exist. Therefore, each experimenter must develop systems and procedures that are both appropriate and correct. We hope that the concepts introduced in this chapter will help the reader to better understand the detailed presentations found in later chapters.
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Tinker, N.A., Robert, L.S., Butler, G., Harris, L.J. (2003). Data Pre-Processing Issues in Microarray Analysis. In: Berrar, D.P., Dubitzky, W., Granzow, M. (eds) A Practical Approach to Microarray Data Analysis. Springer, Boston, MA. https://doi.org/10.1007/0-306-47815-3_2
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DOI: https://doi.org/10.1007/0-306-47815-3_2
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