Year: 2026
Type: article
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.
Source: MethodsX
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,260
Funder: Svenska Forskningsrådet Formas
OpenAlex ID: W7223171247