Abstract
BackgroundDNA microarrays open up a new horizon for studying the genetic determinants of disease. The high throughput nature of these arrays creates an enormous wealth of information, but also poses a challenge to data analysis. Inferential problems become even more pronounced as experimental designs used to collect data become more complex. An important example is multigroup data collected over different experimental groups, such as data collected from distinct stages of a disease process. We have developed a method specifically addressing these issues termed Bayesian ANOVA for microarrays (BAM). The BAM approach uses a special inferential regularization known as spike-and-slab shrinkage that provides an optimal balance between total false detections and total false non-detections. This translates into more reproducible differential calls. Spike and slab shrinkage is a form of regularization achieved by using information across all genes and groups simultaneously.ResultsBAMarray™ is a graphically oriented Java-based software package that implements the BAM method for detecting differentially expressing genes in multigroup microarray experiments (up to 256 experimental groups can be analyzed). Drop-down menus allow the user to easily select between different models and to choose various run options. BAMarray™ can also be operated in a fully automated mode with preselected run options. Tuning parameters have been preset at theoretically optimal values freeing the user from such specifications. BAMarray™ provides estimates for gene differential effects and automatically estimates data adaptive, optimal cutoff values for classifying genes into biological patterns of differential activity across experimental groups. A graphical suite is a core feature of the product and includes diagnostic plots for assessing model assumptions and interactive plots that enable tracking of prespecified gene lists to study such things as biological pathway perturbations. The user can zoom in and lasso genes of interest that can then be saved for downstream analyses.ConclusionBAMarray™ is user friendly platform independent software that effectively and efficiently implements the BAM methodology. Classifying patterns of differential activity is greatly facilitated by a data adaptive cutoff rule and a graphical suite. BAMarray™ is licensed software freely available to academic institutions. More information can be found at .
Highlights
DNA microarrays open up a new horizon for studying the genetic determinants of disease
Multigroup data The issues become more complex for multigroup data collected over different experimental groups, such as data collected from distinct stages of a disease process, or time course experiments in which microarrays are used to track gene expression profiles over time
Illustrative example: tracking the genomic stagewise development of liver metastatic colon cancer As preliminary illustration and motivation for BAMarrayTM, we look at expression data from a large microarray repository of colon cancer tissue samples comprising various stages of tumor progression
Summary
DNA microarrays open up a new horizon for studying the genetic determinants of disease. DNA microarray technology allows researchers to estimate the relative expression levels of thousands of genes simultaneously over different time points, different experimental conditions, or different tissue samples. It is the relevant abundance of the mRNA genetic product that provides surrogate information about the relative abundance of the cell's proteins. In two-group problems, the total number of misclassified genes can be derived in closed form assuming normally distributed data [11] Such calculations suggest that when the fraction of truly differentially expressing genes is relatively low, total misclassification of differential effects will be large unless FDR is controlled at a high value, putting into question the value of such control
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