Papex
q-bio.GN

基因组学

DNA测序和组装;基因和基序发现; RNA编辑和选择性剪接;基因组结构和过程(复制、转录、甲基化等);突变过程。

共 1 篇

q-bio
2609.30013v1
Najla Abassi, Annekathrin Silvia Nedwed, Federico Marini

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).

提交于 Sep 25, 2026