Predicts gestational age using placental DNA methylation microarray data

predictAge Multiplies the coefficients from one of three epigenetic gestational age clocks, by the corresponding CpGs in a supplied betas data.frame.

predictAge(betas, type = "RPC")

Arguments

betas

An n by m dataframe of methylation values on the beta scale (0, 1), where the CpGs are arranged in rows, and samples in columns. Should contain all CpGs used in each clock

type

One of the following: "RPC" (Robust), "CPC", (Control) or "RRPC" (Refined Robust).

Value

A vector of length m, containing inferred gestational age.

Details

Predicts gestational age using one of 3 placental gestational age clocks: RPC, CPC, or refined RPC. Requires placental DNA methylation measured on the Infinium 27K/450k/EPIC methylation array. Ensure as many predictive CpGs are present in your data, otherwise accuracy may be impacted.

It's recommended that you have all predictive CpGs, otherwise accuracy may vary.

Examples

# Load placenta DNAm data
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
data(plBetas)
data(plPhenoData)

plPhenoData %>%
    mutate(inferred_ga = predictAge(plBetas, type = "RPC"))
#> 558 of 558 predictors present.
#> # A tibble: 24 × 8
#>    sample_id  sex    disease      gestation_wk ga_RPC ga_CPC ga_RRPC inferred_ga
#>    <fct>      <chr>  <chr>               <dbl>  <dbl>  <dbl>   <dbl>       <dbl>
#>  1 GSM1944936 Male   preeclampsia           36   38.5   38.7    38.7        38.5
#>  2 GSM1944939 Male   preeclampsia           32   33.1   34.2    32.6        33.1
#>  3 GSM1944942 Female preeclampsia           32   34.3   35.1    33.3        34.3
#>  4 GSM1944944 Male   preeclampsia           35   35.5   36.7    35.5        35.5
#>  5 GSM1944946 Female preeclampsia           38   37.6   37.6    36.6        37.6
#>  6 GSM1944948 Female preeclampsia           36   36.8   38.4    36.7        36.8
#>  7 GSM1944949 Female preeclampsia           37   38.2   38.1    37.7        38.2
#>  8 GSM1944950 Male   preeclampsia           35   35.9   38.0    35.1        35.9
#>  9 GSM1944951 Female normal/heal…           39   40.2   41.0    39.6        40.2
#> 10 GSM1944952 Male   normal/heal…           38   39.7   39.6    39.5        39.7
#> # ℹ 14 more rows