Downstream processing laboratory methods

While only -10% of microarray datasets address the problem of batch effects (48), the degree of error contributed by batch effects may be significant. Batch effects may include experimental variations introduced due to multiple types of technical bias (e.g., time, laboratory, reagents, handling). Analysis of multiple methods to address batch effects has been addressed for precision, accuracy, and overall performance (48). Once probe set raw intensities have been processed via normalization and possible additional corrective measures, values can be used for downstream analyses in identifying differentially expressed genes and corresponding functional associations. 

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