rplec: An R package of placental epigenetic clock to estimate aging by DNA-methylation-based gestational age

rplec is an R package designed to estimate placental aging based on gestational age using DNA methylation levels, so called placental epigenetic clock (PlEC). We developed a PlEC for the 2024 Placental Clock DREAM Challenge (https://www.synapse.org/Synapse:syn59520082/wiki/628063). Our PlEC achieved the top performance based on an independent test set. PlEC can be used to identify accelerated/decelerated aging of placenta for understanding placental dysfunction-related conditions, e.g., great obstetrical syndromes including preeclampsia, fetal growth restriction, preterm labor, preterm premature rupture of the membranes, late spontaneous abortion, and placental abruption.

Features

Normalize DNA methylation values: We provided normalization feature based on beta mixture quantile (BMIQ) method before using a PlEC.
Estimate DNA-methylation-based gestational age: A PlEC is available for estimating gestational age.
Perform quality control: A user can evaluate the PlEC accuracy based on calibration plot, root mean squared error (RMSE), mean absolute error (MAE), and correlation coefficient (Pearson’s r) before interpreting the DNA-methylation-based gestational age to identify placental aging.
Identify placental aging: Compare placental aging based on DNA-methylation-based gestational age between condition of interest and control.

Installation

You can install rplec from CRAN with:

install.packages("rplec")

You can install the development version of rplec from GitHub with:

# install.packages("devtools")
devtools::install_github("herdiantrisufriyana/rplec")

Quick Start

Load necessary packages.

library(rplec)

Load our example data.

beta_values_case <- load_beta_values_case()

Normalize DNA methylation values.

norm_beta_values_case <- bmiq_norm_450k(beta_values_case)

Estimate DNA-methylation-based gestational age.

dnam_ga_case <- plec(norm_beta_values_case)

Vignettes

Explore detailed examples and methodologies in the following vignettes:

Placental Aging Analysis: A data analysis pipeline to identify placental aging using rplec.
Reference Manual: Comprehensive documentation of all functions and features available in rplec. Ideal for detailed reference and advanced use cases.

License

rplec is licensed under the MIT license. See the LICENSE file for more details.

Citation

If you use rplec in your research, please consider citing it:

@misc{rplec2025,
  author = {Herdiantri Sufriyana and Emily Chia-Yu Su},
  title = {rplec: An R package of placental epigenetic clock to estimate aging by DNA-methylation-based gestational age},
  year = {2025},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\\url{https://github.com/herdiantrisufriyana/rplec}}
}

Contact

For questions or support, please contact herdi[at]nycu.edu.tw.

Programming Environment

System requirements

Install Docker desktop once in your machine. Start the service every time you build this project image or run the container.

Installation guide

Build the project image once for a new machine (currently support AMD64 and ARM64).

docker build -t rplec --load .

Run the container every time you start working on the project. Change left-side port numbers for either Rstudio or Jupyter lab if any of them is already used by other applications.

In terminal:

docker run -d -p 8787:8787 -p 8888:8888 -v "$(pwd)":/home/rstudio/project --name rplec_container rplec

In command prompt:

docker run -d -p 8787:8787 -p 8888:8888 -v "%cd%":/home/rstudio/project --name rplec_container rplec

Instructions for use

Rstudio

Change port number in the link, accordingly, if it is already used by other applications.

Visit http://localhost:8787. Username: rstudio Password: 1234

Your working directory is ~/project.

Jupyter lab

Use terminal/command prompt to run the container terminal.

docker exec -it rplec_container bash

In the container terminal, run jupyter lab using this line of codes.

jupyter-lab --ip=0.0.0.0 --no-browser --allow-root

Click a link in the results to open jupyter lab in a browser. Change port number in the link, accordingly, if it is already used by other applications.