SUMO {SUMO} | R Documentation |
SUMO provides tools for simulating complex multi-omics data, allowing researchers to generate datasets that reflect the biological intricacies found in real-world data. This package aims to fill a gap in current omics research by providing users with flexible and customizable tools for generating synthetic data that can be used for method development, benchmarking of Multi-Omics methods.
Key features of SUMO include:
Simulating Multi-Omics Data: Generate multi-layered datasets with customizable structures.
Flexible Data Generation: Control over various simulation parameters such as the sample, noise levels, and signal positions.
Visualization Tools: Functions to visualize simulated data, including scatterplots, histogram, heatmaps and 3D visualization.
Key functions include:
OmixCraftHD()
: Generates synthetic multi-omics datasets based on user-defined parameters.
plot_simData
: Visualizes the structure of the generated data
plot_factor
: Visualizes the raw factor scores, for visual identification of signal noise
plot_weights
: Visualizes the raw features loadings, for visual identification of signal noise
A list containing synthetic multi-omics datasets, which may include several omics layers such as gene expression, proteomics, methylation, etc. Each layer is represented as a matrix or data frame where rows correspond to samples and columns correspond to features.
Maintainer: Bernard Isekah Osang'ir Bernard.Osangir@sckcen.be (ORCID)
Authors:
Bernard Isekah Osang'ir bernard.osangir@uhasselt.be