feature_selection_two

Dividing features to create vectors with signal in the second omic

Provides tools to simulate multi-omics datasets with predefined signal structures. The generated data can be used for testing, validating, and benchmarking integrative analysis methods such as factor models and clustering approaches. This version includes enhanced signal customization, visualization tools (scatter, histogram, 3D), MOFA-based analysis pipelines, PowerPoint export, and statistical profiling of datasets. Designed for both method development and teaching, SUMO supports real and synthetic data pipelines with interpretable outputs. Tini, Giulia, et al (2019) <doi:10.1093/bib/bbx167>.

Bernard Isekah Osang'ir

SUMO

Generating Multi-Omics Datasets for Testing and Benchmarking

Ziv Shkedy

Surya Gupta

Jürgen Claesen

feature_selection_two function

<dl><dt>n_features_two</dt>
<dd>number of features of second omic</dd>
<dt>num.factor</dt>
<dd>type of factors - single or multiple</dd>
<dt>no_factor</dt>
<dd>number of factors</dd></dl>

Arguments

Dividing features to create vectors with signal in the second omic — feature_selection_two

<dl>

<dt>n_features_two</dt>
<dd>number of features of second omic</dd>


<dt>num.factor</dt>
<dd>type of factors - single or multiple</dd>


<dt>no_factor</dt>
<dd>number of factors</dd>

</dl>

feature_selection_two: Dividing features to create vectors with signal in the second omic

Description

Usage

Arguments