CimpleG DNAm benchmarking datasets for cell-type classification and deconvolution

Zenodo (CERN European Organization for Nuclear Research)

Abstract

Two large DNAm benchmarking datasets specifically gathered and curated for cell-type classification and deconvolution problems. It includes a leukocytes dataset and a somatic cells dataset in the GenomicRatioSet format from the minfi package. These can be easily loaded into R with the CimpleG::load_object function. Each dataset includes therein sample data like GEO accession numbers, sample name or ID in their original dataset, cell-type label, one-hot encoded data for each cell-type, preferred train/test splits, and others.

Authors 4

1. Tiago Maié Aachen Institute for Computational Genomics Joint Research Centre for Computational Biomedicine (JRC-COMBINE)

   RWTH Aachen University

   Affiliation as printed

   Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074 Aachen, Germany

2. Myriam Erz Aachen Institute for Computational Genomics Joint Research Centre for Computational Biomedicine (JRC-COMBINE)

   RWTH Aachen University

   Affiliation as printed

   Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074 Aachen, Germany

3. Wolfgang Wagner Aachen

   RWTH Aachen University

   Affiliation as printed

   Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074 Aachen, Germany

4. Ivan G. Costa Aachen Institute for Computational Genomics Joint Research Centre for Computational Biomedicine (JRC-COMBINE)

   RWTH Aachen University

   Affiliation as printed

   Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074 Aachen, Germany