The w4mclassfilter R package provides the computational back-end of a Galaxy tool to complement Workflow4Metabolomics (W4M). This package (and the corresponding Galaxy tool) perform several steps, either to reduce the number samples or features to be analyzed, or to address several data issues that may impede downstream statistical analysis: Samples that are missing from either sampleMetadata or dataMatrix are eliminated. Samples may also be eliminated by a "sample class" column in sampleMetadata. Features that are missing from either variableMetadata or dataMatrix are eliminated. Features may be eliminated by specifying minimum or maximum value (or both) allowable in columns of variableMetadata. Features may be eliminated by specifying minimum or maximum intensity (or both) allowable in columns of dataMatrix for at least one sample for each feature ("range of row-maximum for each feature"). Missing values in dataMatrix are imputed either to zero (by default) or to the result of a user-supplied imputation function. Features and samples that have zero variance are eliminated. Samples and features have consistent order in variableMetadata, sampleMetadata, and dataMatrix. The column for sorting variableMetadata or sampleMetadata may be specified or defaults to the first column. By default, the names of the first columns of variableMetadata and sampleMetadata are set respectively to "variableMetadata" and "sampleMetadata" An advanced option enables producing a "center" for each treatment in lieu of the samples for each treatment. Changes in version 0.98.15 NEW FEATURES Enhancement https://github.com/HegemanLab/w4mclassfilter/issues/6 - "compute center for each treatment" INTERNAL MODIFICATIONS Built with R 3.6.1 (2019-07-05) "Action of the Toes" Built with the command R CMD build w4mclassfilter to assure that vignettes are built as intended.