Dataset Information

FuntooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types.

ABSTRACT: DNA methylation patterns are well known to vary substantially across cell types or tissues. Hence, existing normalization methods may not be optimal if they do not take this into account. We therefore present a new 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. Benefits of cell (tissue)-specific normalization are demonstrated in three data sets. Improvement can be substantial; it is strikingly better on chromosome X, where methylation patterns have unique inter-tissue variability.An R package is available at https://github.com/GreenwoodLab/funtooNorm, and has been submitted to Bioconductor at http://bioconductor.org.

SUBMITTER: Oros Klein K

PROVIDER: S-EPMC4743629 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types.

Oros Klein Kathleen K Grinek Stepan S Bernatsky Sasha S Bouchard Luigi L Ciampi Antonio A Colmegna Ines I Fortin Jean-Philippe JP Gao Long L Hivert Marie-France MF Hudson Marie M Kobor Michael S MS Labbe Aurelie A MacIsaac Julia L JL Meaney Michael J MJ Morin Alexander M AM O'Donnell Kieran J KJ Pastinen Tomi T Van Ijzendoorn Marinus H MH Voisin Gregory G Greenwood Celia M T CM

Bioinformatics (Oxford, England) 20151024 4

<h4>Motivation</h4>DNA methylation patterns are well known to vary substantially across cell types or tissues. Hence, existing normalization methods may not be optimal if they do not take this into account. We therefore present a new 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.<h4>Results</h4>funtooNorm is relevant ...[more]

PMID: 26500152

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Project description:BackgroundMicroRNA (miRNA) expression is broadly altered in cancer, but few studies have investigated miRNA deregulation in oral squamous cell carcinoma (OSCC). Epigenetic mechanisms are involved in the regulation of >30 miRNA genes in a range of tissues, and we aimed to investigate this further in OSCC.MethodsTaqMan® qRT-PCR arrays and individual assays were used to profile miRNA expression in a panel of 25 tumors with matched adjacent tissues from patients with OSCC, and 8 control paired oral stroma and epithelium from healthy volunteers. Associated DNA methylation changes of candidate epigenetically deregulated miRNA genes were measured in the same samples using the MassArray® mass spectrometry platform. MiRNA expression and DNA methylation changes were also investigated in FACS sorted CD44(high) oral cancer stem cells from primary tumor samples (CSCs), and in oral rinse and saliva from 15 OSCC patients and 7 healthy volunteers.ResultsMiRNA expression patterns were consistent in healthy oral epithelium and stroma, but broadly altered in both tumor and adjacent tissue from OSCC patients. MiR-375 is repressed and miR-127 activated in OSCC, and we confirm previous reports of miR-137 hypermethylation in oral cancer. The miR-200 s/miR-205 were epigenetically activated in tumors vs normal tissues, but repressed in the absence of DNA hypermethylation specifically in CD44(high) oral CSCs. Aberrant miR-375 and miR-200a expression and miR-200c-141 methylation could be detected in and distinguish OSCC patient oral rinse and saliva from healthy volunteers, suggesting a potential clinical application for OSCC specific miRNA signatures in oral fluids.ConclusionsMiRNA expression and DNA methylation changes are a common event in OSCC, and we suggest miR-375, miR-127, miR-137, the miR-200 family and miR-205 as promising candidates for future investigations. Although overall activated in OSCC, miR-200/miR-205 suppression in oral CSCs indicate that cell specific silencing of these miRNAs may drive tumor expansion and progression.

Dataset Information

FuntooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types.

Publications

funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types.

Similar Datasets

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