FlexArray is a Microsoft Windows software package for statistical analysis of microarray data. Currently, the analysis of Affymetrix GeneChip ® and Illumina BeadChip ® expression arrays is supported.

The main strong points of this software are

● Runs on Microsoft Windows

●  Support for Affymetrix GeneChip ® arrays and support for Illumina BeadChip ® expression arrays

●  Easy to use data import

●  Intuitive visual representation of the data analysis process in the form of an "analysis pipeline"

●  Comprehensive collection of statistical data processing algorithms, built on the framework of Bioconductor:

●Preprocessing and normalization: MAS 5, RMA, PLIER, GC-RMA, dChip, and Custom for Affymetrix, lumi for Illumina

●Statistical testing: t-test, ANOVA, LPE, SAM, Empirical Bayes, Bayes T, cyber-T

●Fold-change and group statistics calculations

●False discovery rate: FDR (Benjamini Hochberg and Benjamini Yekutieli), FWER (Holm, Hochberg, Sidak Single Step, Sidak Step Down, and Bonferroni)

●Description of every algorithm and every parameter

●If an algorithm is not available in a particular context, FlexArray will provide a detailed description of the reason why.

●  Plug-in architecture for algorithms: end-users can easily integrate new analysis methods into the software

●  A wide variety of plots applicable to every level of the analysis:

●Quality Control plots for raw data, including spot intensity maps, QQ-plots, scatter plots, histograms, and box plots

●Plots for normalized data and for sample means, including scatter plots, QQ plots, MvA plots, and histograms

●PCA plots for quick assessment of the experiment

●Plots for statistical test results, including Volcano plots, and histograms

●A number of innovative plots, e.g. the shiv plot combining a box plot with a signal intentity histogram and a data variance curve

●A number of plots specifically designed to facilitate comparisons between various analysis methods, e.g. the CAT plot, or the overabundance plot

●Venn diagrams to compare gene lists

●Description of every plot

●  Plots can be zoomed in, panned, and exported to a number of formats, including EPS

●  Plug-in architecture for plots: it is quite easy to add a new plot to the program

●  Context-sensitive data table with such features as sorting, filtering, search, export, column resizing and reordering, etc.

●  Flexible annotation import

●  Gene list generation, management, and visualization

●  Tools to compare outputs of multiple analysis methods

●  Full analysis history, including the values of all parameters used in algorithms, full execution log, and remembering the exact form of the R script used

●  Re-usable analysis protocols: create an analysis schema once and then re-use it for your subsequent experiments, or pass it on to your colleagues

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