epiage_estimation: Estimates age in skeletal muscle from calibrated DNA...
In MEAT: Muscle Epigenetic Age Test

Description Usage Arguments Details Value See Also Examples

epiage_estimation takes as input a SummarizedExperiment-class object whose assays contain a beta-matrix called "beta". This beta-matrix should contain DNA methylation profiles in skeletal muscle that have been cleaned with clean_beta and calibrated with BMIQcalibration. epiage_estimation will use the muscle clock to estimate epigenetic age in each sample.

1	epiage_estimation(SE = NULL, version = "MEAT2.0", age_col_name = NULL)

`SE`	A `SummarizedExperiment-class` object. The "assays" component of `SE` should contain a beta-matrix of DNA methylation beta-values called "beta" that has been cleaned with `clean_beta` and calibrated with `BMIQcalibration`. `SE` may optionally contain annotation information on the CpGs stored in "rowData" and sample phenotypes stored in "colData".
`version`	A character specifying which version of the epigenetic clock you would like to use. Dy default, `version` is set to "MEAT2.0" for the second version of the epigenetic clock. If you would like to use the original version, set `version` to "MEAT".
`age_col_name`	The name of the column in colData from `SE` that contains age (in years).

epiage_estimation estimates epigenetic age for each sample in the input SE based on DNA methylation profiles. SE needs to be a SummarizedExperiment-class object containing a matrix of beta-values called "beta" in assays. Beta must have been calibrated to the gold standard GSE50498 using BMIQcalibration to obtain good estimates of epigenetic age.

A SummarizedExperiment-class object identical to the input SE, with components added to colData. If no phenotypes were provided in the colData of the input SE, epiage_estimation will put in colData a tibble containing a single column called "DNAmage", corresponding to epigenetic age (in years) for each sample. If phenotypes were provided in the colData of the input SE, epiage_estimation will add to the existing colData three columns:

DNAmage epigenetic age (in years)
AAdiff the difference between predicted and actual age (in years).
AAresid the residuals of a linear model (using lm) of DNAmage against actual age. AAresid is only returned if the number of samples is > 2, as AAresid cannot be calculated with < 2 samples.

BMIQ for the original BMIQ algorithm, https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-10-r115 for the adapted version of the BMIQ algorithm, and https://onlinelibrary.wiley.com/doi/full/10.1002/jcsm.12556 for the elastic net model of the muscle clock.

# Load matrix of beta-values of two individuals from dataset GSE121961
data("GSE121961", envir = environment())
# Load phenotypes of the two individuals from dataset GSE121961
data("GSE121961_pheno", envir = environment())

# Create a SummarizedExperiment object to coordinate phenotypes and
# methylation into one object.
library(SummarizedExperiment)
GSE121961_SE <- SummarizedExperiment(assays=list(beta=GSE121961),
colData=GSE121961_pheno)

# Run clean_beta() to clean the beta-matrix
GSE121961_SE_clean <- clean_beta(SE = GSE121961_SE,
version = "MEAT2.0")

# Run BMIQcalibration() to calibrate the clean beta-matrix
GSE121961_SE_calibrated <- BMIQcalibration(SE = GSE121961_SE_clean,
version = "MEAT2.0")

# Run epiage_estimation() to obtain DNAmage + optionally AAdiff and AAresid
GSE121961_SE_epiage <- epiage_estimation(SE = GSE121961_SE_calibrated,
version = "MEAT2.0",
age_col_name = "Age")
colData(GSE121961_SE_epiage)