EchoGO: annotation-context-aware functional interpretation of transcriptomic data

MethodsX, vol. 17, pp. 104222

Abstract

Functional enrichment of transcriptomic datasets is often constrained by uneven annotation depth, incomplete genomic resources, and uncertainty about the most informative reference species. EchoGO is a reproducible downstream workflow that integrates bias-aware GOseq results with g:Profiler enrichment across reference contexts after orthology-supported preparation of identifiers and annotations. Instead of merging ortholog-derived terms into gene-level annotations, EchoGO analyses each reference context independently and assembles support at the GO-term level while preserving tool, organism, panel, and background-mode provenance. The workflow accepts differential-expression results, background gene sets, annotation mappings, and GOseq outputs, and generates consensus tables, ontology-level visualisations, semantic-reduction outputs, enrichment networks, and HTML reports for de novo and reference-based studies. Conservative background-aware evidence from native GOseq and custom-background g:Profiler is reported separately from exploratory no-background results. Evaluation used three RNA-seq contrasts spanning a reference-rich zebrafish exercise and two non-model Gammarus pulex field contrasts. EchoGO distinguished terms recovered by native GOseq, a standard single-reference analysis, and multi-reference panels. When additional terms were recovered, their provenance was retained, turning broader recovery into documented functional hypotheses that can be examined and prioritised rather than an undifferentiated enrichment list. EchoGO therefore supports transparent interpretation when GO-term recovery depends on reference context, annotation depth, and background definition.

Authors 4

1. Camilo Escobar-Sierra corresponding Aachen Chair of Ecotoxicology and Environmental Risk Assessment Institute for Environmental Research

   RWTH Aachen University

   Affiliation as printed

   Chair of Ecotoxicology and Environmental Risk Assessment, Institute for Environmental Research, RWTH Aachen University, Aachen, Germany

2. Felix Langschied

   Goethe University Frankfurt

   Affiliation as printed

   Institute of Cell Biology and Neuroscience, Applied Bioinformatics Group, Goethe University Frankfurt, Frankfurt am Main, Germany

3. Angelina Miller Aachen Chair of Ecotoxicology and Environmental Risk Assessment Institute for Environmental Research

   RWTH Aachen University

   Affiliation as printed

   Chair of Ecotoxicology and Environmental Risk Assessment, Institute for Environmental Research, RWTH Aachen University, Aachen, Germany

4. Pedro A. Inostroza Aachen Chair of Ecotoxicology and Environmental Risk Assessment Institute for Environmental Research

   University of Gothenburg · RWTH Aachen University

   Affiliation as printed

   Chair of Ecotoxicology and Environmental Risk Assessment, Institute for Environmental Research, RWTH Aachen University, Aachen, Germany

   Department of Biological and Environmental Science, University of Gothenburg, Gothenburg, Sweden