cell_composition: Cell composition
In hhhh5/ewastools_releases: EWAS Tools
estimateLC R Documentation
Cell composition
Description
Estimation of cell proportions for blood and saliva using the Houseman algorithm
Usage
estimateLC(meth, ref, constrained = FALSE)
Arguments
meth
Matrix of beta values
ref
Choice of reference dataset: available options are 'HRS' (Health and Retirement Study), 'Reinius' [2]', Bakulski' [3],
'deGoede' [4], 'Gervin'[5], 'Lin' [6], 'Mill' [GSE103541], 'Salas' [7], 'Lolipop' [8] or
combinations of them, concatenated by '+', e.g. 'Reinius+Lin' (you might have to flip first and
second name)). Furthermore, the option 'saliva' and 'salivaEPIC' are available [9].
constrained
Force that all cell proportions sum up to 1.
Value
Estimated cell proportions B-lymphocytes, CD4 T-cells, CD8 T-cells, granulocytes, monocytes, natural killer cells (and nucleated red blood cells) using the Houseman algorithm [1]. Models were trained on various reference datasets of purified cell types.
References
Houseman EA, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC bioinformatics. 2012 Dec 1;13(1):86.
Reinius LE, et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PloS one. 2012 Jul 25;7(7):e41361.
Bakulski KM, et al. DNA methylation of cord blood cell types: applications for mixed cell birth studies. Epigenetics. 2016 May 3;11(5):354-62.
de Goede OM, et al. Nucleated red blood cells impact DNA methylation and expression analyses of cord blood hematopoietic cells. Clinical epigenetics. 2015 Dec;7(1):95.
Gervin K, et al. Cell type specific DNA methylation in cord blood: A 450K-reference data set and cell count-based validation of estimated cell type composition. Epigenetics. 2016 Sep 1;11(9):690-8
Gervin K, et al. Systematic evaluation and validation of reference and library selection methods for deconvolution of cord blood DNA methylation data. bioRxiv. 2019 March; DOI:10.1101/570457
Salas LA, et al. An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray. Genome biology. 2018 Dec;19(1):64.
Heiss JA, et al. Training a model for estimating leukocyte composition using whole-blood DNA methylation and cell counts as reference. Epigenomics. 2017 Jan;9(1):13-20.
Middleton LYM, et al. Saliva cell type DNA methylation reference panel for epidemiology studies in children. 2020 Sep;
hhhh5/ewastools_releases documentation built on Feb. 7, 2024, 2:57 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| estimateLC | R Documentation |
Cell composition
Description
Estimation of cell proportions for blood and saliva using the Houseman algorithm
Usage
estimateLC(meth, ref, constrained = FALSE)
Arguments
meth |
Matrix of beta values |
ref |
Choice of reference dataset: available options are 'HRS' (Health and Retirement Study), 'Reinius' [2]', Bakulski' [3], 'deGoede' [4], 'Gervin'[5], 'Lin' [6], 'Mill' [GSE103541], 'Salas' [7], 'Lolipop' [8] or combinations of them, concatenated by '+', e.g. 'Reinius+Lin' (you might have to flip first and second name)). Furthermore, the option 'saliva' and 'salivaEPIC' are available [9]. |
constrained |
Force that all cell proportions sum up to 1. |
Value
Estimated cell proportions B-lymphocytes, CD4 T-cells, CD8 T-cells, granulocytes, monocytes, natural killer cells (and nucleated red blood cells) using the Houseman algorithm [1]. Models were trained on various reference datasets of purified cell types.
References
Houseman EA, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC bioinformatics. 2012 Dec 1;13(1):86.
Reinius LE, et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PloS one. 2012 Jul 25;7(7):e41361.
Bakulski KM, et al. DNA methylation of cord blood cell types: applications for mixed cell birth studies. Epigenetics. 2016 May 3;11(5):354-62.
de Goede OM, et al. Nucleated red blood cells impact DNA methylation and expression analyses of cord blood hematopoietic cells. Clinical epigenetics. 2015 Dec;7(1):95.
Gervin K, et al. Cell type specific DNA methylation in cord blood: A 450K-reference data set and cell count-based validation of estimated cell type composition. Epigenetics. 2016 Sep 1;11(9):690-8
Gervin K, et al. Systematic evaluation and validation of reference and library selection methods for deconvolution of cord blood DNA methylation data. bioRxiv. 2019 March; DOI:10.1101/570457
Salas LA, et al. An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray. Genome biology. 2018 Dec;19(1):64.
Heiss JA, et al. Training a model for estimating leukocyte composition using whole-blood DNA methylation and cell counts as reference. Epigenomics. 2017 Jan;9(1):13-20.
Middleton LYM, et al. Saliva cell type DNA methylation reference panel for epidemiology studies in children. 2020 Sep;
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.