An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray

Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylat...

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Published inGenome Biology Vol. 19; no. 1; p. 64
Main Authors Salas, Lucas A., Koestler, Devin C., Butler, Rondi A., Hansen, Helen M., Wiencke, John K., Kelsey, Karl T., Christensen, Brock C.
Format Journal Article
LanguageEnglish
Published London BioMed Central 29.05.2018
Springer Nature B.V
BMC
Subjects
Accuracy
Algorithms
Animal Genetics and Genomics
B-cells
B-lymphocytes
Bioinformatics
Biomedical and Life Sciences
Blood
Blood Cells - metabolism
CD4 antigen
CD8 antigen
CD8-positive T-lymphocytes
CpG Islands
Datasets
Deoxyribonucleic acid
DNA
DNA Methylation
Epigenetics
Ethnicity
Evolutionary Biology
Gene expression
Gene Library
Genetic testing
genome
Genomes
Human Genetics
Humans
Life Sciences
Lymphocytes
Lymphocytes B
Lymphocytes T
Male
Method
Microbial Genetics and Genomics
Monocytes
Natural killer cells
Neutrophils
Oligonucleotide Array Sequence Analysis
Plant Genetics and Genomics
B-cells
Monocytes
Helper T-cells
Cytotoxic T-lymphocytes
Neutrophils
DNA methylation
Epigenetics
Adults
Natural killer cells
Leukocytes
Online AccessGet full text
ISSN1474-760X
1474-7596
1474-760X
DOI10.1186/s13059-018-1448-7

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Abstract Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R 2  = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.
AbstractList Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R2 = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.
Abstract Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R2 = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.
Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R2 = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R2 = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.
Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R  = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.
Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R 2  = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.
Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R² = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.
ArticleNumber 64
Author Koestler, Devin C.
Hansen, Helen M.
Kelsey, Karl T.
Christensen, Brock C.
Butler, Rondi A.
Salas, Lucas A.
Wiencke, John K.
Author_xml – sequence: 1
  givenname: Lucas A.
  surname: Salas
  fullname: Salas, Lucas A.
  organization: Department of Epidemiology, Geisel School of Medicine, Dartmouth College
– sequence: 2
  givenname: Devin C.
  surname: Koestler
  fullname: Koestler, Devin C.
  organization: Department of Biostatistics, University of Kansas Medical Center
– sequence: 3
  givenname: Rondi A.
  surname: Butler
  fullname: Butler, Rondi A.
  organization: Departments of Epidemiology and Pathology and Laboratory Medicine, Brown University
– sequence: 4
  givenname: Helen M.
  surname: Hansen
  fullname: Hansen, Helen M.
  organization: Department of Neurological Surgery, Institute for Human Genetics, University of California San Francisco
– sequence: 5
  givenname: John K.
  surname: Wiencke
  fullname: Wiencke, John K.
  organization: Department of Neurological Surgery, Institute for Human Genetics, University of California San Francisco
– sequence: 6
  givenname: Karl T.
  surname: Kelsey
  fullname: Kelsey, Karl T.
  organization: Departments of Epidemiology and Pathology and Laboratory Medicine, Brown University
– sequence: 7
  givenname: Brock C.
  surname: Christensen
  fullname: Christensen, Brock C.
  email: Brock.C.Christensen@dartmouth.edu
  organization: Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Departments of Molecular and Systems Biology, and Community and Family Medicine, Geisel School of Medicine, Dartmouth College
BackLink https://www.ncbi.nlm.nih.gov/pubmed/29843789$$D View this record in MEDLINE/PubMed
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Issue 1
Keywords B-cells
Monocytes
Helper T-cells
Cytotoxic T-lymphocytes
Neutrophils
DNA methylation
Epigenetics
Adults
Natural killer cells
Leukocytes
Language English
License Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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Snippet Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries...
Abstract Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference...
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StartPage 64
SubjectTerms Accuracy
Algorithms
Animal Genetics and Genomics
B-cells
B-lymphocytes
Bioinformatics
Biomedical and Life Sciences
Blood
Blood Cells - metabolism
CD4 antigen
CD8 antigen
CD8-positive T-lymphocytes
CpG Islands
Datasets
Deoxyribonucleic acid
DNA
DNA Methylation
Epigenetics
Ethnicity
Evolutionary Biology
Gene expression
Gene Library
Genetic testing
genome
Genomes
Human Genetics
Humans
Life Sciences
Lymphocytes
Lymphocytes B
Lymphocytes T
Male
Method
Microbial Genetics and Genomics
Monocytes
Natural killer cells
Neutrophils
Oligonucleotide Array Sequence Analysis
Plant Genetics and Genomics
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Title An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray
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