Below is a "simple" graphical representation of
the normalization algorithm for M.A.N.
(microarray analysis and normalization)


VIEW lowess algorithm
HOWTO to analyze your data






First, normalize each subarray by the users normalization choice:

Second, normalize each subarray by the average
intensity of all genes per subarray:



Below is a sample MA scatter plot of
gene intensities after normalizing the
subarrays to the users normalization preference.




Next the sample MA scatter plot of
gene intensities after normalizing the
subarrays using lowess.

Now that the data is centered around zero
we can use a one-sided T-test to measure the distance (deviation) of the
gene intensities from zero. This will produce more accurate p-values
and allow users to determine which genes are up or down regulated.



VIEW lowess algorithm
HOWTO to analyze your data