An algorithm called cell-rPLR for the identification of outliers in single cells of a data matrix is proposed. The algorithm is designed for metabolomic data, where due to the size effect the measured values are not directly comparable. Pairwise log-ratios between the variable values form the elemental information for the algorithm, and the aggregation of appropriate weights results in outlyingness information. A further feature of cell-rPLR is that it is useful for biomarker identification, particularly in presence of cellwise outliers. Package is based on paper: 'Cellwise outlier detection and biomarker identification in metabolomics based on pairwise log-ratios', Walach J., Filzmoser P., Kouril S., Submitted
|Maintainer||Jan Walach <[email protected]>|
|License||GNU General Public License v3.0|
|Package repository||View on GitHub|
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