Signature matrix

RNA-expression signature matrix reference

 

CD4

- GSE107011 (2019) : RNA-Seq profiling of 29 immune cell types and peripheral blood mononuclear cells

- GSE113891 (2018) : Transcriptomic profile of circulating CD4+ T cells from TCM and TEM memory compartments from donors vaccinated at birth either with whole or acellular Pertussis vaccine

- GSE114407 (2018) : Cell type specific gene expression patterns associated with posttraumatic stress disorder in World Trade Center responders

- GSE115978 (2018) : Single-cell RNA-seq of melanoma ecosystems reveals sources of T cells exclusion linked to immunotherapy clinical outcomes

 

CD8

- GSE98638 (2017) : Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing

- GSE114407 (2018)

- GSE107011 (2019)

 

B_

- GSE107011 (2019)

- GSE114407 (2018)

- GSE115978 (2018)

 

mono

- GSE114407 (2018)

- GSE107011 (2019)

 

NK

- GSE107011 (2019)

- GSE115978 (2018)

 

Endo

- GSE102767 (2018) : GATA2 is Dispensable for Generation of Hemogenic Endothelium But Required for Endothelial-to-Hematopoietic Transition

- GSE113839 (2018) : RNA-seq from HNSCC and melanoma populations

- GSE115978 (2018) : Single-cell RNA-seq of melanoma ecosystems reveals sources of T cells exclusion linked to immunotherapy clinical outcomes

 

Fibro

- GSE113839 (2018)

- GSE109448 (2018) : RNA-seq analysis of freshly isolated synovial fibroblast subsets from patients with rheumatoid arthritis

- GSE109449 (2018) : Single cell RNA-seq analysis of freshly isolated synovial fibroblasts in patients with rheumatoid arthritis or osteoarthritis

 

Neutro

- GSE107011 (2019)

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Methylation signature matrix reference

 

Cell-line

- GSE68379 (2016) : The landscape of pharmacogenomic interactions in human cancer

 

B_

- GSE110554 (2018) : FlowSorted.Blood.EPIC: An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray (II)

- GSE49618 (2013) : Sorted normal bone marrow cells from healthy volunteers at Washington University

- GSE35069 (2012) : Differential DNA Methylation in Purified Human Blood Cells

- GSE88824 (2017) : Deconvolution of whole blood DNA methylomes reveals immune cell type-specific differential methylation in Multiple Sclerosis

 

CD8

- GSE110554 (2018)

- GSE35069 (2012) : Differential DNA Methylation in Purified Human Blood Cells

- GSE88824 (2017)

 

endothelial

- GSE82234 (2017) : DNA methylation profiles of human umbilical vein endothelial cells (HUVECs)

- GSE144804 (2020) : Global CpG methylation analysis of primary endothelial cells before and after TNFa stimulation

 

monocyte, neutrophil, NK cells, eosinophils

- GSE35069 (2012)

- GSE88824 (2017)

 

glia

- GSE66351 (2018) : DNA methylation profiling of neuron and glia for the dissection of cell type, age and Alzheimer’s disease-specific changes in the human brain

 

neurons

- GSE98203 (2017) : DNA methylation profiling of human prefrontal cortex neurons in heroin users shows significant difference between genomic contexts of hyper- and hypomethylation and a younger epigenetic age

- GSE66351 (2018)

 

CD4 T-cells and Treg

- GSE49667 (2013) : DNA methylation differences between human regulatory T cells and conventional T cells

- GSE59290 (2016) : DNA Methylation Analysis of Systemic Lupus Erythematosus

 

CD14, CD19, Tmem, Tnaive

- GSE59290 (2016)

- GSE71837 (2015) : Comparison of the DNA methylation profiles of CD14+ monocytes from human peripheral blood with DCs and MACs obtained by exposure with GM-CSF/IL-4 and GM-CSF, respectively, and with mature DCs and MACs after LPS exposure CD14+ monocytes

 

non-CpGs

- GSE31848 (2012) : Recurrent Variations in DNA Methylation in Human Pluripotent Stem Cells and their Differentiated Derivatives [Illumina Infinium 450K DNA Methylation]

- GSE59091 (2016) : Non-CG DNA methylation is a biomarker for assessing endodermal differentiation capacity in pluripotent stem cells

- GSE68134 (2015) : DNA methylation profiles of fibroblasts and induced pluripotent stem cells (iPSCs) from individuals with Zellweger spectrum disorder (ZSD), a class of peroxisome biogenesis disorder, and healthy controls

 

Ground truth

- GSE77797 (2016) : DNA methylation profiling of whole blood and reconstructed mixtures of purified leukocytes isolated from human adult blood

# Ground truth fractions from reconstructed mixtures of purified human leukocytes and FACs fractions from adult human whole blood.

Accession   Status         CD4 T  CD8 T  B Cell  NK Cell  Monocyte  Granulocyte  Total
GSM2059592  Reconstructed  13%    11%    16%     12%      23%       25%          100%
GSM2059593  Reconstructed  7%     19%    19%     15%      19%       21%          100%
GSM2059594  Reconstructed  6%     33%    8%      11%      19%       23%          100%
GSM2059595  Reconstructed  16%    29%    7%      15%      22%       11%          100%
GSM2059596  Reconstructed  11%    20%    20%     22%      10%       17%          100%
GSM2059597  Reconstructed  18%    13%    26%     15%      22%       6%           100%
GSM2059598  Reconstructed  13%    2%     1%      4%       5%        75%          100%
GSM2059599  Reconstructed  16%    11%    1%      2%       7%        63%          100%
GSM2059600  Reconstructed  9%     6%     2%      0%       10%       73%          100%
GSM2059601  Reconstructed  14%    8%     2%      3%       6%        67%          100%
GSM2059602  Reconstructed  12%    5%     6%      7%       4%        66%          100%
GSM2059603  Reconstructed  15%    4%     4%      2%       5%        70%          100%
GSM2059604  Whole Blood    24%    12%    7%      2%       5%        40%          91%
GSM2059605  Whole Blood    12%    6%     4%      3%       6%        66%          97%
GSM2059606  Whole Blood    18%    10%    5%      5%       5%        47%          89%
GSM2059607  Whole Blood    16%    15%    6%      5%       9%        44%          95%
GSM2059608  Whole Blood    18%    6%     2%      2%       6%        59%          93%
GSM2059609  Whole Blood    11%    5%     4%      3%       6%        68%          96%

ground_truth.txt

0.00MB

 

 

Reference

- A review of digital cytometry methods: estimating the relative abundance of cell types in a bulk of cells (2021), https://doi.org/10.1093/bib/bbaa219

- Immune cell deconvolution of bulk DNA methylation data reveals an association with methylation class, key somatic alterations, and cell state in glial/glioneuronal tumors (2021), https://doi.org/10.1186/s40478-021-01249-9

- Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL) (2016), https://doi.org/10.1186/s12859-016-0943-7

- A Landscape of Pharmacogenomic Interactions in Cancer (2016), https://doi.org/10.1016/j.cell.2016.06.017

- MethylResolver—a method for deconvoluting bulk DNA methylation profiles into known and unknown cell contents (2020), https://doi.org/10.1186/s40478-021-01249-9