CurveFit takes a vector of chipdata from microarray slides and fits the data to a Gaussian distribution through a non-linear least-squares optimization algorithm.The results are graphically depicted in a series of histograms. Each histogram represents a different initial seed (left to right: 2 bins, 3 bins, 4 bins, 4.5 bins, 5 bins, and 5.5 bins) that is passed to the curve fitting algorithm. The resulting fit for each histogram is superimposed with a solid blue line.The user is then able to visually select the 'best' fit.
a vector of chipdata from microarray slides.
plot can take values of 1 or 0. If plot is 1 then the histogram with the curve fit will be shown graphically.
an object res which is a list containing the following components. res1]: mean of the computed background. res: standard deviation of the computed background.
Choudary L Jagarlamudi
Dozmorov I,Centola,M. An associative analysis of gene expression array data. Bioinformatics.2003 Jan22;19(2):204-11
Knowlton N,Dozmorov I, Centola M. Microarray data Analysis Tool box(MDAT): for normalization,adjustment and analysis of gene expression data. Bioonformatics.2004 Dec 12;20(18):3687-90
#see normalize for details.
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