A variance-stabilizing transformation for gene-expression microarray data

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A variance-stabilizing transformation for gene-expression microarray data

MOTIVATION Standard statistical techniques often assume that data are normally distributed, with constant variance not depending on the mean of the data. Data that violate these assumptions can often be brought in line with the assumptions by application of a transformation. Gene-expression microarray data have a complicated error structure, with a variance that changes with the mean in a non-l...

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Approximate Variance-stabilizing Transformations for Gene-expression Microarray Data

MOTIVATION A variance stabilizing transformation for microarray data was recently introduced independently by several research groups. This transformation has sometimes been called the generalized logarithm or glog transformation. In this paper, we derive several alternative approximate variance stabilizing transformations that may be easier to use in some applications. RESULTS We demonstrate...

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A gene-expression microarray datum is modeled as an exponential expression signal (log-normal distribution) and additive noise. Variance-stabilizing transformation based on this model is useful for improving the uniformity of variance, which is often assumed for conventional statistical analysis methods. However, the existing method of estimating transformation parameters may not be perfect bec...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2002

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/18.suppl_1.s105