YASMA - Yet Another Statistical Microarray Analysis: "YASMA is an add-on library for the R statistical package and can be used to analyse simple replicated experiments. For example, we are interested in bacterial genes over- or under-expressed in mutants as compared to the wild type. For this purpose, multiple mRNA preparations are hybridized on several arrays. As long as the same number of arrays is used for each preparation a straightforward ANOVA analysis and analysis of variance components can be applied to the series of experiments (a balanced factorial design).
At the moment the package contains
* Routines for inspecting the correlation between array replicates and for removing low expression genes that cause low correlation.
* A method for interpolating missing data using estimates from an ANOVA analysis.
* Routines for fast ANOVA analysis of data typical for microarrays experiments (balanced factorial designs with nested factors). The design matrix for such analysis is usually very large (due to the effects involving genes) and cannot be dealt with efficiently by standard ANOVA routines based on design matrix evaluations.
* Routines for an analysis of variance components: cultures, arrays, etc are random representatives of possible experiments and need to be analyzed in a slightly different way than by simple ANOVA.
* A routine to caculate the optimal design of an experiment based on relative costs of cultures, arrays, etc, and on estimates of variability from a prior experiment.
* Calculation of p-values derived from the results of the analysis of variance components. If residuals show different amounts of variance (which is often the case), hierarchical bootstrapping of residuals is a more reliable way to derive p-values.
* Implementations of additional standard tests (t-statistic) and of Newton's et. al hierarchical model methods (see below the Statistics Notes) for multiple experiments."
