An R package for normalization of data from the Illumina Infinium Human Methylation450 BeadChip (Illumina 450 K) built on the concepts in the recently published funNorm method, and introducing cell-type or tissue-type flexibility. funtooNorm is relevant for data sets containing samples from two or more cell or tissue types. A visual display of cross-validated errors informs the choice of the optimal number of components in the normalization. Improved normalization of datasets containing multiple tissues can be expected to translate into increased power to detect associations of interest, due to the inferred reduction in residual error; funNorm and this extension funtooNorm are designed with this goal in mind.

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Unix/Linux, Mac OS, Windows
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funtooNorm support




  • (Oros Klein et al., 2015) funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types. Bioinformatics.
    PMID: 26500152


Lady Davis Institute, Jewish General Hospital, Montreal, QC H3T 1E2, Canada; Ludmer Center for Neuroinformatics and Mental Health, McGill University Health Centre, McGill University, Montreal, QC H4A 3J1, Canada

Funding source(s)

This work was supported by the Ludmer Center for Neuroinformatics & Mental Health, and by the Canadian Institutes of Health Research operating grant MOP-300545.

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