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Research PaperResearchia:202609.25016

EMMA: an R/Bioconductor package to automate tracking of metadata in functional enrichment analyses

Najla Abassi

Abstract

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 integra...

Submitted: September 25, 2026Subjects: Biology; Biotechnology

Description / Details

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).


Source: arXiv:2609.30013v1 - http://arxiv.org/abs/2609.30013v1 PDF: https://arxiv.org/pdf/2609.30013v1 Original Link: http://arxiv.org/abs/2609.30013v1

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Submission Info
Date:
Sep 25, 2026
Topic:
Biotechnology
Area:
Biology
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