EchoGO: Traceable Functional Interpretation Across Annotation Contexts

Zenodo (CERN European Organization for Nuclear Research)

Abstract

EchoGO helps researchers interpret transcriptomic responses through biologically relevant annotation resources while keeping the experiment and its target GOseq evidence central. It supports both reference-rich studies and annotation-limited de novo transcriptomes. What changes in this release Traceable evidence: Target only, Target + context and Context-derived hypotheses replace composite-score interpretation. Every GO term retains its analysis/context provenance and source-local statistics. Explicit biological choices: declare selected contexts, their rationale and the target context (or its absence). The same resolved experimental foreground/background is submitted across contexts; context-specific recognition and effective domains are recorded. Separate exploration: the optional default-domain g:Profiler tier stays outside the primary evidence profiles and downstream primary products. Interpretation tools: separate RRvGO semantic products, gene-sharing networks and a richer HTML report help navigate the functional landscape. A fuller first experience: an offline cached demo, updated guides, reference-based preparation documentation and migration guidance make the workflow easier to try. Try it Install the attached EchoGO_0.1.4.tar.gz source package following the public README's dependency instructions. Then run: library(EchoGO) demo <- echogo_quickstart(run_demo = TRUE, full = TRUE, live_gprofiler = FALSE) The demo uses cached g:Profiler evidence and opens the biological report in an interactive session. Own-data enrichment uses the online service; see the README for explicit inputs and context configuration. Documentation and citation Use the public README for installation and first analysis, browseVignettes("EchoGO") for installed guides, and NEWS.md for detailed changes. Historical API names containing consensus remain for compatibility; retired composite scores are not recreated. Software: GPL-3.

Authors 4

1. Camilo Escobar-Sierra 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

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

4. Pedro A. Inostroza 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; Department of Biological and Environmental Science, University of Gothenburg, Gothenburg, Sweden