compute_diffmeans_sumvar

Compute diff mean sum var dataframe

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

compute_diffmeans_sumvar function

<dl><dt>data</dt>
<dd>Matrix with beta values that will be used to compute diffmeans sumvar data frame</dd>
<dt>target_vector</dt>
<dd>boolean vector defining which samples in data are part of the target class</dd></dl>

Arguments

Compute diff mean sum var dataframe — compute_diffmeans_sumvar

<dl>

<dt>data</dt>
<dd>Matrix with beta values that will be used to compute diffmeans sumvar data frame</dd>


<dt>target_vector</dt>
<dd>boolean vector defining which samples in data are part of the target class</dd>

</dl>

compute_diffmeans_sumvar: Compute diff mean sum var dataframe

Description

Usage

Value

Arguments