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MethPed: an R package for the identification of pediatric brain tumor subtypes

Journal article
Authors MT Ahamed
Anna Danielsson
S. Nemes
Helena Carén
Published in Bmc Bioinformatics
Volume 17
Issue 1
Pages 262
ISSN 1471-2105
Publication year 2016
Published at Institute of Clinical Sciences, Department of Oncology
Sahlgrenska Cancer Center
Institute of Biomedicine, Department of Pathology
Pages 262
Language en
Keywords DNA methylation, 450K, Random forest, R package, Glioblastoma, Medulloblastoma, Ependymoma, Classifier (classification tool), Astrocytoma, MethPed, Biochemistry & Molecular Biology, Biotechnology & Applied Microbiology, Mathematical & Computational Biology
Subject categories Cancer and Oncology


Background: DNA methylation profiling of pediatric brain tumors offers a new way of diagnosing and subgrouping these tumors which improves current clinical diagnostics based on histopathology. We have therefore developed the MethPed classifier, which is a multiclass random forest algorithm, based on DNA methylation profiles from many subgroups of pediatric brain tumors. Results: We developed an R package that implements the MethPed classifier, making it easily available and accessible. The package can be used for estimating the probability that an unknown sample belongs to each of nine pediatric brain tumor diagnoses/subgroups. Conclusions: The MethPed R package efficiently classifies pediatric brain tumors using the developed MethPed classifier. MethPed is available via Bioconductor:

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