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2015 ; 4
(4
): 432-53
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A Synthetic Kinome Microarray Data Generator
#MMPMID27600233
Maleki F
; Kusalik A
Microarrays (Basel)
2015[Oct]; 4
(4
): 432-53
PMID27600233
show ga
Cellular pathways involve the phosphorylation and dephosphorylation of proteins.
Peptide microarrays called kinome arrays facilitate the measurement of the
phosphorylation activity of hundreds of proteins in a single experiment.
Analyzing the data from kinome microarrays is a multi-step process. Typically,
various techniques are possible for a particular step, and it is necessary to
compare and evaluate them. Such evaluations require data for which correct
analysis results are known. Unfortunately, such kinome data is not readily
available in the community. Further, there are no established techniques for
creating artificial kinome datasets with known results and with the same
characteristics as real kinome datasets. In this paper, a methodology for
generating synthetic kinome array data is proposed. The methodology relies on
actual intensity measurements from kinome microarray experiments and preserves
their subtle characteristics. The utility of the methodology is demonstrated by
evaluating methods for eliminating heterogeneous variance in kinome microarray
data. Phosphorylation intensities from kinome microarrays often exhibit such
heterogeneous variance and its presence can negatively impact downstream
statistical techniques that rely on homogeneity of variance. It is shown that
using the output from the proposed synthetic data generator, it is possible to
critically compare two variance stabilization methods.
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