estimateLC: Estimation of Leukocyte composition for whole blood samples
In normalize450K: Preprocessing of Illumina Infinium 450K data

Description Usage Arguments Details Value Author(s) References

View source: R/estimateLC.R

Estimate leukocyte composition from whole blood DNA methylation

1	estimateLC(eSet)

eSet

A Biobase eSet object as returned from a call of normalize450K

Cell proportions are estimated using the algorithm developed by Houseman et al. (2012) by two different models. The first model was trained on a dataset of purified leukocytes (Reinius et al., 2012) and provides predictions for six cell types (granulocytes, monocytes, CD8+ T cells, CD4+ T cells, natural killer cells and CD19+ B cells), the second model was trained on whole blood samples from the LOLIPOP study as described by Heiss et al. (2016) and provides predictions for 4 cell types (neutrophils, eosinophils, lymphocytes, monocytes – ignore the prediction for basophils). Use this function only for normalized data (with normalize450K(...,tissue='Blood').

Returns the eSet object with cell proportions estimates added to the phenoData slot.

Jonathan A. Heiss

Houseman EA, et al. (2012) DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics, doi:10.1186/1471-2105-13-86

Reinius LE, et al. (2012) Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PloS ONE, doi:10.1371/journal.pone.0041361

Heiss JA, et al. (2016). Training a model for estimating leukocyte composition using whole-blood DNA methylation and cell counts as reference. Epigenomics, doi:10.2217/epi-2016-0091

normalize450K documentation built on Nov. 8, 2020, 5:55 p.m.