CARMA: A platform for analyzing microarray datasets that incorporate replicate measures.
BACKGROUND
The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust experimental design coupled with an analysis of variance (ANOVA) incorporating a model that accounts for known sources of experimental variability can significantly improve the determination of differences in gene expression and estimations of their significance.


RESULTS
To realize the full benefits of performing analysis of variance on microarray data we have developed CARMA, a microarray analysis platform that reads data files generated by most microarray image processing software packages, performs ANOVA using a user-defined linear model, and produces easily interpretable graphical and numeric results. No pre-processing of the data is required and user-specified parameters control most aspects of the analysis including statistical significance criterion. The software also performs location and intensity dependent lowess normalization, automatic outlier detection and removal, and accommodates missing data.


CONCLUSIONS
CARMA provides a clear quantitative and statistical characterization of each measured gene that can be used to assess marginally acceptable measures and improve confidence in the interpretation of microarray results. Overall, applying CARMA to microarray datasets incorporating repeated measures effectively reduces the number of gene incorrectly identified as differentially expressed and results in a more robust and reliable analysis.
Biomedical Engineering Program, Genomics Research Laboratory, University of Arizona, Tucson, Arizona 85724, USA. kgreer@u.arizona.edu
Kevin A
KA
Greer
Matthew R
MR
McReynolds
Heddwen L
HL
Brooks
James B
JB
Hoying
D000704:Analysis of Variance; D000818:Animals; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D003198:Computer Simulation / Q000706:statistics & numerical data; D030541:Databases, Genetic / Q000706:statistics & numerical data; D051379:Mice; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*