BAMarray Bayesian analysis of variance for microarrays
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BAMarray Tags

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BAMarray Description

BAMarray is an advanced and professional application that implements the BAM tehcnique. BAM is a new statistical technique for detecting differentially expressing genes from microarray data. At the heart of the method is a special type of signal detection technique that squashes down false signal while leaving real signal alone. Standard methods look for genes by relying on elementary test statistics using data from one gene at a time (such as t-tests, or contrasts from ANOVA models). Gene lists are obtained by filtering statistics by attempting to control overall type-I error, or false discovery rate, or by filtering using a user specified cutoff level. BAM takes a fundamentally different approach and focuses instead on estimating the differential effect of a gene by synthesizing information across all genes simultaneously. Rather than filtering genes, estimated effects are mapped into pattern types. BAM's special signal detection mechanism shrinks to zero estimated effects for genes unlikely to be differentially expressing, and consequently patterns of interest become highly interpretable using graphical visualization tools. Patterns of interest might be "hit-and-run" genes which affect a biologic system for only a certain amount of time, or genes involved throughout the process. BAM applies to multigroup experimental designs, such as data collected over different stages of a disease. Other applications include gene expression time profiling for time-course data, outlier detection, invariant set normalization, gene atlas transcriptome mappings, as well an many other problems. Main features: BAMarray is a user friendly Java application that runs on different operating systems. BAMarray can also be run unattended in Batch Mode initiated by a script file. Batch Mode can process several data files sequentially and save the resulting analysis to disk. Writing custom designed scripts allow users to interface with different types of software, such as Bioconductor, and R. BAMarray has a Save Run feature allowing users to save the results of a run for later retrieval. A run that can take minutes to execute can be restored in only seconds using Restore Run. Save Run can also be triggered in Batch Mode. Experimental designs with unlimited groups are accommodated. Visualization plots are available for identifying specific types of gene patterns. BAMarray automatically classifies genes into gene patterns. BAMarray is nearly automatic, and free of complicated tuning parameters. Most statistical methods require a user specified filtering value for identifying significant genes. BAMarray provides an automated value. Unequal variances across genes and experimental groups are systematically handled by an automated pre-processing step that does not artificially dampen or amplify group differences across genes (as seen with other transformations, such as logarithms). Graphical tools using zoom-in and lassoing allow users to interactively generate lists of genes. Gene labels can be toggled on or off allowing genes of interest to be readily identified. Specific genes can be highlighted using a drop down list or by populating a tracking list from gene labels found in an existing file. Gene lists can be exported. Exporting lists can be automated using Batch Mode. Figures can be saved as publication quality color graphics. Plots for testing the underlying assumptions of the model are included as part of the graphics suite. Supports JRE 6.

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