Title |
Identification and systematic annotation of tissue-specific differentially methylated regions using the Illumina 450k array
|
---|---|
Published in |
Epigenetics & Chromatin, August 2013
|
DOI | 10.1186/1756-8935-6-26 |
Pubmed ID | |
Authors |
Roderick C Slieker, Steffan D Bos, Jelle J Goeman, Judith VMG Bovée, Rudolf P Talens, Ruud van der Breggen, H Eka D Suchiman, Eric-Wubbo Lameijer, Hein Putter, Erik B van den Akker, Yanju Zhang, J Wouter Jukema, P Eline Slagboom, Ingrid Meulenbelt, Bastiaan T Heijmans |
Abstract |
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) from Illumina 450k chip data for four peripheral tissues (blood, saliva, buccal swabs and hair follicles) and six internal tissues (liver, muscle, pancreas, subcutaneous fat, omentum and spleen with matched blood samples). |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 33% |
United Kingdom | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 67% |
Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 2 | <1% |
United Kingdom | 2 | <1% |
Spain | 2 | <1% |
Uruguay | 1 | <1% |
New Zealand | 1 | <1% |
Denmark | 1 | <1% |
Belgium | 1 | <1% |
Nigeria | 1 | <1% |
United States | 1 | <1% |
Other | 0 | 0% |
Unknown | 200 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 70 | 33% |
Researcher | 48 | 23% |
Student > Master | 21 | 10% |
Student > Doctoral Student | 13 | 6% |
Professor > Associate Professor | 12 | 6% |
Other | 32 | 15% |
Unknown | 16 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 84 | 40% |
Biochemistry, Genetics and Molecular Biology | 36 | 17% |
Medicine and Dentistry | 30 | 14% |
Computer Science | 12 | 6% |
Neuroscience | 10 | 5% |
Other | 18 | 8% |
Unknown | 22 | 10% |