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If you haven’t installed CimpleG, you can find the instructions to do so here. However it should be as simple as:
We load the CimpleG package.
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: .
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
)
#> Training for target 'blood_cells' with 'CimpleG' has finished.: 1.563 sec elapsed
#> Training for target 'hepatocytes' with 'CimpleG' has finished.: 0.441 sec elapsedHere we are generating signatures to find leukocytes and hepatocytes.
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$plotThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.