DNAmGA {methylclock} | R Documentation |
Gestational DNAm age estimation using different DNA methylation clocks.
DNAmGA( x, toBetas = FALSE, fastImp = FALSE, normalize = FALSE, age, cell.count = TRUE, cell.count.reference = "andrews and bakulski cord blood", min.perc = 0.8, ... )
x |
data.frame (Individual in columns, CpGs in rows, CpG names in first colum - i.e. Horvath's format), matrix (individuals in columns and Cpgs in rows having CpG names in the rownames), ExpressionSet or GenomicRatioSet. |
toBetas |
Should data be transformed to beta values? Default is FALSE. If TRUE, it implies data are M values. |
fastImp |
Is fast imputation performed if necessary? (see details). Default is FALSE |
normalize |
Is Horvath's normalization performed? By default is FALSE |
age |
individual's chronological age. Required to compute gestational age difference output |
cell.count |
Are cell counts estimated? Default is TRUE. |
cell.count.reference |
Used when 'cell.count' is TRUE. Default is "blood gse35069 complete". See 'meffil::meffil.list.cell.count.references()' for possible values. |
min.perc |
Indicates the minimum conicidence percentage required between CpGs in or dataframee x and CpGs in clock coefficients to perform the calculation. If min.prec is too low, the estimated gestational DNAm age can be poor |
... |
Other arguments to be passed through impute package |
Imputation is performed when having missing data. Fast imputation is performed by ... what about imputing only when CpGs for the clock are missing?
the estimated gestational DNAm age
TestDataset <- get_TestDataset() TestDataset[1:5, ] ga.test <- DNAmGA(TestDataset)