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Series GSE110554 Query DataSets for GSE110554
Status Public on May 08, 2018
Title FlowSorted.Blood.EPIC: An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray (II)
Organism Homo sapiens
Experiment type Methylation profiling by genome tiling array
Summary DNA methylation assessments of peripheral blood DNA can be used to accurately estimate the relative proportions of underlying leukocyte subtypes. Such cell deconvolution analysis relies on libraries of discriminating differentially methylated regions that are developed for each specific cell type measured. The relationship between estimated cell type proportions can then be tested for their association with phenotypes, disease states, and subject outcomes, or used in multivariable models as terms for adjustment in epigenome-wide association studies (EWAS). We obtained purified neutrophils, monocytes, B-lymphocytes, natural killer (NK) cells, CD4+ T-cells, and CD8+ T-cells from healthy subjects and measured DNA methylation with the Illumina HumanMethylationEPIC array platform. In addition, we measured DNA methylation with the EPIC array in two sets of artificial DNA mixtures comprising the above cell types. We compared three separate approaches to select reference differentially methylated region libraries (DMR library), for cell type proportion inference. The IDOL algorithm identified an optimal DMR library consisting of 450 CpG sites for inferring leukocyte subtype proportions (average R2=99.2). Importantly, the majority of CpG sites (69%) in the IDOL DMR library were unique to the new EPIC methylation array, in that they were not present on the 450K array. Our new reference DMR library is available as a Bioconductor package, has the potential to reduce any unintended technical differences arising from the combination of different generations of array platforms, and may be helpful in generating larger DMR libraries that include novel cell subtypes.
Overall design Bisulphite converted DNA from neutrophils (Neu, n=6), monocytes (Mono, n=6), B-lymphocytes (Bcells, n=6), CD4+ T-cells (CD4T, n=7, six samples and one technical replicate), CD8+ T-cells (CD8T, n=6), Natural Killer cells (NK, n=6), and 12 DNA artificial mixtures (labeled as MIX in the dataset) were hybridised to the Illumina Infinium HumanMethylationEPIC Beadchip v1.0_B4
Contributor(s) Salas LA, Koestler DC, Butler RA, Hansen HM, Wiencke JK, Kelsey KT, Christensen BC
Citation(s) 29843789, 35140201, 36127421
NIH grant(s)
Grant ID Grant title Affiliation Name
R01 CA052689 Genetic and molecular epidemiology of adult glioma University of California San Francisco John K. Wiencke
P50 CA097257 BRAIN TUMOR SPORT GRANT University of California San Francisco John K. Wiencke
R01 CA207110 Prospective immune profiling using methylation markers and pancreatic cancer risk TUFTS UNIVERSITY BOSTON Karl Timothy Kelsey
R01 DE022772 MicroRNA related genetic variation and head and neck cancer DARTMOUTH COLLEGE Brock Clarke Christensen
P20 GM104416 Early Risk Factor Related Epigenetic Alterations in Breast Cancer Pathogenesis DARTMOUTH COLLEGE Brock Clarke Christensen
R01 CA216265 (PQ3) Immune epigenetic biomarkers of bladder cancer outcomes DARTMOUTH COLLEGE Brock Clarke Christensen
Submission date Feb 13, 2018
Last update date Oct 04, 2022
Contact name Lucas A. Salas
Organization name Geisel School of Medicine at Dartmouth
Department Epidemiology
Lab Salas Lab
Street address 1 Medical Center Dr, DHMC
City Lebanon
State/province NH
ZIP/Postal code 03756
Country USA
Platforms (1)
GPL21145 Infinium MethylationEPIC
Samples (49)
GSM2998021 PCA0612
GSM2998022 NKpan2510
GSM2998023 WB1148
This SubSeries is part of SuperSeries:
GSE110555 SuperSeries: An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray
BioProject PRJNA433986

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE110554_RAW.tar 851.3 Mb (http)(custom) TAR (of IDAT)
GSE110554_signals.txt.gz 204.2 Mb (ftp)(http) TXT
Processed data included within Sample table

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