Track genomics, neuroscience and molecular biology.
Search papers, labs, and topics across Lattice.
To resolve persistent reproducibility bottlenecks in functional enrichment analyses (FEA), the authors developed EMMA, an R/Bioconductor package that automatically records execution-time provenance metadata across standard bioinformatics pipelines. Incomplete reporting of dynamic annotation databases, software versions, and runtime parameters regularly prevents the replication and auditing of omics interpretations. The package integrates non-invasively into existing Bioconductor workflows to log, audit, and export exact database releases and operational parameters without requiring users to rewrite legacy code.
Most functional enrichment analyses silently fail reproducibility standards due to untracked database drift and parameter omissions—a vulnerability EMMA solves by automating full-stack runtime provenance tracking across Bioconductor pipelines.
Summary: Functional enrichment analysis (FEA) is a widely used approach for interpreting high-throughput omics data. However, essential methodological details, such as software versions, analysis parameters, and annotation database releases among others, are often incompletely reported, limiting the reproducibility and transparency of enrichment analyses and complicating the assessment of potentially problematic methodological choices. Here we present EMMA, an R/Bioconductor package that integrates with existing FEA tools and automatically captures provenance metadata, such as annotation metadata, software version, and parameters, during the analysis runtime. Our package provides utilities for accessing and exporting the recorded metadata to facilitate transparent reporting and preserve provenance required for reproducible enrichment analyses. This also enables auditing of the results while remaining compatible with existing Bioconductor workflows. Availability and implementation: EMMA is available on Bioconductor under the MIT license (https: //bioconductor.org/packages/EMMA), with its development version also available on GitHub (https: //github.com/imbeimainz/EMMA).