predict.CimpleG

Predict outcome from a CimpleG signatures on new data

DNA methylation signatures are usually based on multivariate
approaches that require hundreds of sites for predictions. 'CimpleG'
is a method for the detection of small CpG methylation signatures used
for cell-type classification and deconvolution. 'CimpleG' is time
efficient and performs as well as top performing methods for cell-type
classification of blood cells and other somatic cells, while basing
its prediction on a single DNA methylation site per cell type (but
users can also select more sites if they so wish). Users can train
cell type classifiers ('CimpleG' based, and others) and directly apply
these in a deconvolution of cell mixes context. Altogether, 'CimpleG'
provides a complete computational framework for the delineation of
DNAm signatures and cellular deconvolution. For more details see Maié
et al. (2023) <doi:10.1186/s13059-023-03000-0>.

Tiago F.V. Maié

CimpleG

A Method to Identify Single CpG Sites for Classification and
Deconvolution

predict.CimpleG function

<dl><dt>object</dt>
<dd>CimpleG object.</dd>
<dt>...</dt>
<dd>Not used at the moment.</dd>
<dt>new_data</dt>
<dd>Data to be predicted, samples should be in rows and features in columns.
Last column of `new_data` should have the target/class labels coded as 0 or 1.</dd>
<dt>class_labels</dt>
<dd>Class labels of new data if these are not provided directly with it.</dd></dl>

Arguments

Predict outcome from a CimpleG signatures on new data — predict.CimpleG

<dl>

<dt>object</dt>
<dd>CimpleG object.</dd>


<dt>...</dt>
<dd>Not used at the moment.</dd>


<dt>new_data</dt>
<dd>Data to be predicted, samples should be in rows and features in columns.
Last column of `new_data` should have the target/class labels coded as 0 or 1.</dd>


<dt>class_labels</dt>
<dd>Class labels of new data if these are not provided directly with it.</dd>

</dl>

predict.CimpleG: Predict outcome from a CimpleG signatures on new data

Description

Usage

Value

Arguments