Generate signatures

In CimpleG: A Method to Identify Single CpG Sites for Classification and Deconvolution

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

CimpleG (Simple CpG signatures)

• CimpleG tries to find the CpGs that best classify a cell-type given a train dataset
• It also enables you to perform cell-type deconvolution in a couple of easy steps
• It can use beta or M values
• Here we show how easy it is to generate a signatures

Installation

If you haven't installed CimpleG, you can find the instructions to do so here. However it should be as simple as:

if (!require("CimpleG")) devtools::install_github("costalab/CimpleG")

Loading package

We load the CimpleG package.

library("CimpleG")

Loading data

In this tutorial, we will use a small dataset with just 409 samples and 1000 CpGs. We will also use a table with metadata regarding these samples. This dataset comes included with CimpleG. You can read more about it here: .

# load data
data(train_data)
data(train_targets)

Running CimpleG

Running CimpleG can be quite simple. You just need to run the CimpleG function with a few parameters.

# run CimpleG
cimpleg_result <- CimpleG(
  train_data,
  train_targets,
  target_columns = c("blood_cells", "hepatocytes"),
  train_only = TRUE
)

Here we are generating signatures to find leukocytes and hepatocytes.

Plotting CimpleG CpG signature

We can quickly visualize how our signature is able to separate the data.

sig_plt <-
  signature_plot(
    cimpleg_result,
    train_data,
    train_targets,
    sample_id_column = "gsm",
    true_label_column = "cell_type"
  )
sig_plt$plot

CimpleG documentation built on Dec. 7, 2025, 1:07 a.m.