DNA methylation signatures predict cytogenetic subtype and outcome in pediatric acute myeloid leukemia (AML)
type: Dataset
distribution: Landing page for the dataset
description: This dataset contains genome-wide DNA methylation data generated from 142 pediatric acute myeloid leukemia (AML) samples originating from bone marrow or peripheral blood samples taken at AML diagnosis (N=123) or relapse (N=19). Further details regarding the samples are available in Supplementary Table S1 from Krali and Palle et. al., 2021 (https://doi.org/10.3390/genes12060895). Genome-wide DNA methylation was analyzed at the SNP&SEQ Technology Platform, SciLifeLab, National Genomics Infrastructure Uppsala, Sweden. 200ng 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 Methylprep Python library was used to generate and normalize the beta-value matrix (https://pypi.org/project/methylprep/1.3.3/). The raw idat files along with a samplesheet, processed beta-value matrix, annotation file for CpG annotation, and signal intensities matrix will be made available upon request. Limited phenotype information is available in the Supplemental Table 1 of the manuscript. All scripts that give a walk-through from data preprocessing from the raw idat files until the modelling process with Machine Learning can be found on the following GitHub repository: https://github.com/Molmed/Krali-Palle_2021. 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.se.
modified: 2024-06-26T00:00:00Z
issued: 2024-06-26T00:00:00Z
publisher: Uppsala University
theme: HEAL
access rights: NON PUBLIC
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Olga Krali
    type: Agent
    account: https://orcid.org/0000-0002-6436-9531
    type: PrivateIndividual(s)
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  had role: principalInvestigator
  agent: Josefine Palle
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  agent: Christofer Bäcklin
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  agent: Ulrika Norén-Nyström
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  agent: Henrik Hasle
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  had role: principalInvestigator
  agent: Kirsi Jahnukainen
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    type: PrivateIndividual(s)
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  agent: Randi Hovland
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  had role: principalInvestigator
  agent: Birgitte Lausen
    type: Agent
    type: PrivateIndividual(s)
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  agent: Rolf Larsson
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  agent: Lars Palmqvist
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  had role: principalInvestigator
  agent: Anna Staffas
    type: Agent
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  had role: principalInvestigator
  agent: Bernward Zeller
    type: Agent
    type: PrivateIndividual(s)
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Jessica Nordlund
    type: Agent
    account: https://orcid.org/0000-0001-8699-9959
    type: PrivateIndividual(s)
keyword: Oncology and carcinogenesis not elsewhere classified
keyword: Epigenetics (incl. genome methylation and epigenomics)

Landing page for the dataset
type: Distribution
title: Landningssida för datasetet @sv
access URL: DNA methylation signatures predict cytogenetic subtype and outcome in pediatric acute myeloid leukemia (AML)
availability: stable

Uppsala University
type: Agent
name: Uppsala universitet @sv
type: Academia-ScientificOrganisation
source: https://ror.org/048a87296