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Multimodal classification of molecular subtypes in pediatric acute lymphoblastic leukemia

Multimodal classification of molecular subtypes in pediatric acute lymphoblastic leukemia
https://doi.org/10.17044/SCILIFELAB.22303531
This dataset contains genome-wide DNA methylation data generated from 384 pediatric acute lymphoblastic leukemia (ALL) samples originating from bone marrow or peripheral blood samples taken at ALL diagnosis (n = 384). Further details regarding the samples are available in Supplementary Table S2 from Krali et al., 2023 (https://doi.org/10.1038/s41698-023-00479-5Opens in a new tab). Genome-wide DNA methylation was analyzed at the SNP&SEQ Technology Platform, SciLifeLab, National Genomics Infrastructure Uppsala, Sweden. 250 ng of bisulfite converted DNA was amplified, fragmented and hybridised to Illumina Infinium Human Methylation450k Beadchip using the standard protocol from Illumina (iScan SQ instrument). This metadata record contains information about the raw idat files generated from the Infinium DNA methylation arrays. The raw idat files were processed with Methylation Module (1.8.5) software in Genome Studio (V2010.3). Peak-based correction was used to normalize the beta-value matrix. The raw idat files along with a samplesheet, processed beta-value matrix, annotation file for CpG annotation will be made available upon request. Limited phenotype information is available in the Supplemental Table S2 of the manuscript. All scripts that give a walk-through to our project, including the modelling process with Machine Learning can be found in our GitHub repository (https://github.com/Molmed/Krali_2023Opens in a new tab) . Terms for access The DNA methylation dataset is only to be used for research that is seeking to advance the understanding of the influence of epigenetic factors on leukemia etiology and biology. The data should not be used for other purposes, i.e. investigating the epigenetic signatures that may lead to identification of a person. For retrieving the data used for the scope of this publication, please contact datacentre@scilifelab.seOpens in a new tab.
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https://doi.org/10.17044/SCILIFELAB.22303531

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