Identification and systematic annotation of tissue-specific differentially methylated regions using the Illumina 450k array
Background DNA methylation has been recognized as a key mechanism in cell differentiation. Various studies have compared tissues to characterize epigenetically regulated genomic regions, but due to differences in study design and focus there still is no consensus as to the annotation of genomic regions predominantly involved in tissue-specific methylation. We used a new algorithm to identify and annotate tissue-specific Differentially Methylated Regions (tDMRs) in Illumina 450k chip data on four...
Provenance — who produced it, who reused it
Linked to 16 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- De novo identification of differentially methylated regions in t... 2015 · 1,044 cites
- Identification of tissue-specific cell death using methylation p... 2016 · 621 cites
- DNA Methylation Landscapes of Human Fetal Development 2015 · 110 cites
- Identification of rare de novo epigenetic variations in congenit... 2018 · 100 cites
- Grandmaternal stress during pregnancy and DNA methylation of the... 2017 · 92 cites
- Whole Blood DNA Methylation Signatures of Diet Are Associated Wi... 2020 · 84 cites
- Does Prenatal Stress Shape Postnatal Resilience? – An Epigenome-... 2019 · 74 cites
- A suite of DNA methylation markers that can detect most common h... 2017 · 72 cites
7 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently