I used to perform the normalization of microarray data from Affymatrix platform using RMA method. However the processed data tend to be smaller and the divergence between probes also become smaller. I know the reason is the logarithm. I wanna know the reduction of relative value of probes may affect the discovering the differentiated expressed genes. Or should I use the ratio between value before log?
Question: Microarray Data Normalization Using Rma Method
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Jonathan Hsu • 60 wrote:
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modified 9.5 years ago
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Neilfws ♦ 49k
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9.5 years ago by
Jonathan Hsu • 60
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Neilfws ♦ 49k wrote:
When you take logs of expression values, you need to remember that the value obtained is now in "log base N". So for example if you used log base 2, a difference between values of 1 is actually a 2x difference, a difference between values of 2 = 4x difference and so on. So the smaller ratio between probes under different conditions when logged is not a "bad" thing; it's just a different way to express the numbers.
If there is differential expression, the test used to find it (e.g. p-values or something better, such as SAM) will take the magnitude of the expression values into account. So don't worry if it "looks small" to your eyes.
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