FlexArray is an R based, Microsoft Windows software for statistical analysis of microarray data. Currently, the analysis of Affymetrix GeneChip ®, NimbleGen ® 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 and others
●Statistical testing: t-test, ANOVA, LPE, SAM, Empirical Bayes, Bayes T, cyber-T and many others
●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