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Holomics

License: GPL-3 Project Status: Active - The project has reached a stable, usable state and is being actively developed.

Holomics is an R Shiny application enabling its users to perform single- and multi-omics analyses by providing a user-friendly interface to upload the different omics datasets, select and run the implemented algorithms and finally visualize the generated results.

Holomics is mainly built on the R package mixOmics, which offers numerous algorithms for the integrative analysis of omics datasets. From this repertoire, the single-omics algorithms “Principle Component Analysis” (PCA) and “Partial Least Squares Discriminant Analysis” (PLS-DA), the pairwise-omics analysis “sparse Partial Least Squares” (sPLS) and the multi-omics framework DIABLO (“Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies”) have been implemented in Holomics.

Installation

For the current Holomics version it is very important that you use R 4.2. and check that mixOmics was installed with version 6.22.0.

CRAN

install.packages("Holomics")

Github

# Install devtools if it is not already installed
install.packages("devtools")
library(devtools)

# Install Holomics package 
install_github("https://github.com/MolinLab/Holomics")

Additional packages

You need to install the Bioconductor package separately.

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("mixOmics", version = "6.22.0")
BiocManager::install("BiocParallel")

Start application

Either with

library(Holomics)
run_app()

or

Holomics::run_app()

Workflow

To use all the features offered, the workflow described below should be followed. First, the datasets are uploaded where any pre-filtering/transformation step takes place. Then the user should take the datasets to the single-omics analysis, where key features are identified and the datasets are reduced accordingly. After the single-omics analyses, the user can apply the multi-omics analyses to identify correlations between 2-n datasets. NOTE: If pre-filtered (ideally from Holomics at an earlier stage) datasets have already been uploaded, it is possible to start directly with the multi-omics analysis.

Further information

For further information on how to use Holomics please have a look at our vignette.

These 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.
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