I am reading a book called "Statistics and Data Analysis for Microarrays Using R and Bioconductor". More specifically, I am looking at the limitations of microarrays, and I don't understand this sentence:
"The variance of average chip intensity among spike-in data sets is much lower than those measured in most real-life data sets, casting doubts on the general applicability of these data for developing analytical tools for highly diverse clinical expression profiles."
I have two questions:
- I understand that spike-in data sets are control that you include in your sample preparation, but how do they work when you analyze/transform your data?
- What does the author mean by "the variance of average chip intensity among the spike-in data sets"? I know what variance is. For example, if I have 42 control genes, do I compute the average intensity for all of them for each array and then compute the variance?