By Phillip I. Good

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Extra info for Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

Example text

1. Normalization Before the individual genes can be ranked according to their contributions or conﬁdence intervals used to identify differentially expressed genes, the data must ﬁrst be normalized. Four normalization techniques are in common use. All four techniques assume that all (or most) of the genes in the array have an average expression ratio equal to one. The normalization factor is used to adjust the data to compensate for experimental variability and to balance the ﬂuorescence signals from the samples being compared.

1. 10 A normalization factor can then be calculated and used to rescale the intensity for each gene in the array. 2. Normalization using regression techniques. In a scatterplot of the logarithms of Cy5 versus Cy3 intensities (or their logarithms), genes expressed at similar levels will cluster along a straight line. In closely related samples, the data 10 See Chapter 4 for an explanation of these intensities. Words that are both underlined and italicized are deﬁned in the glossary of biomedical terminology found at the end of this book.

Suppose the goal is to detect the locations and times at which activity during the post-stimulus experiment period differs signiﬁcantly from the background pre-stimulus period. To apply a permutation test, we must ﬁnd permutations of the data that satisfy an exchangeability condition, that is, permutations that leave the distribution of the statistic of interest unaltered under the null hypothesis. Permutations in space and time are not useful for these applications because of spatiotemporal dependence of the noise.