DeeDeeExperiment: Building an infrastructure for integrating and managing omics data analysis results in R/Bioconductor

TL;DR

DeeDeeExperiment is a new R/Bioconductor class designed to organize, store, and manage complex omics analysis results, enhancing reproducibility and data interoperability within a unified framework.

Contribution

It introduces a novel S4 class that extends SingleCellExperiment to integrate differential expression and enrichment results, improving data management in omics research.

Findings

Facilitates organization of multiple contrasts and metadata

Enhances reproducibility and data sharing

Streamlines interpretation of large omics datasets

Abstract

Summary: Modern omics experiments now involve multiple conditions and complex designs, producing an increasingly large set of differential expression and functional enrichment analysis results. However, no standardized data structure exists to store and contextualize these results together with their metadata, leaving researchers with an unmanageable and potentially non-reproducible collection of results that are difficult to navigate and/or share. Here we introduce DeeDeeExperiment, a new S4 class for managing and storing omics data analysis results, implemented within the Bioconductor ecosystem, which promotes interoperability, reproducibility and good documentation. This class extends the widely used SingleCellExperiment object by introducing dedicated slots for Differential Expression (DEA) and Functional Enrichment Analysis (FEA) results, allowing users to organize, store, and retrieve information on multiple contrasts and associated metadata within a single data object, ultimately streamlining the management and interpretation of many omics datasets. Availability and implementation: DeeDeeExperiment is available on Bioconductor under the MIT license (https://bioconductor.org/packages/DeeDeeExperiment), with its development version also available on Github (https://github.com/imbeimainz/DeeDeeExperiment).