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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.
Health stats visible at Monitor.