EchoGO: cross-species consensus enrichment for transcriptomic interpretation

Zenodo (CERN European Organization for Nuclear Research)

Abstract

## EchoGO v0.1.3 EchoGO v0.1.3 improves the reliability, reproducibility, and usability of the complete enrichment workflow. This release strengthens gene-name resolution for g:Profiler, adds a dedicated reference-based input-preparation workflow, makes the packaged demonstration deterministic, and improves dependency handling, reporting, and regression testing. ### Highlights - Restored portable canonical-name resolution for g:Profiler queries: genuine SwissProt gene symbols are prioritised, followed by eggNOG preferred names and portable native symbols. - Raw transcript, contig, seed-ortholog, Ensembl protein, and accession identifiers remain available as mapping provenance but are excluded from submitted g:Profiler vectors. - Added `echogo_prepare_reference_inputs()` for resumable preparation of reference-based RNA-seq inputs from GFF3/GTF files, protein FASTA files, and eggNOG-mapper annotations. - Made the packaged demo deterministic by using explicit canonical inputs, frozen enrichment resources, and clean output directories. - Added direct checks that the quickstart produces a non-empty consensus table and, when requested, a complete HTML report. - Improved automatic input resolution by ranking candidate files, preferring canonical GOseq TSV files, and rejecting ambiguous matches. - Improved GOseq parsing, including preservation of quoted comma-separated `gene_ids` and detection of spill-column corruption. - Updated generated GOseq tables to filter terms using adjusted FDR rather than raw p-values. - Improved installation of OrgDb packages in the active R library, including project-local `renv` environments. - Improved portability of interactive network widgets and packaged HTML reports. - Added `run_rrvgo` controls for deliberately lighter workflow runs. - Expanded offline regression testing for demo execution, input parsing, identifier resolution, dependencies, reference preparation, and quickstart behaviour. ### Installation Install the release directly from GitHub: ```r install.packages(c("remotes", "BiocManager")) remotes::install_github( "miloes114/EchoGo@v0.1.3", build_vignettes = TRUE ) library(EchoGO) Install an organism annotation package for RRvGO: EchoGO::echogo_install_orgdb("org.Mm.eg.db") Run the deterministic packaged demonstration: EchoGO::echogo_quickstart(run_demo = TRUE) For the complete demonstration, including RRvGO, exploratory outputs, evaluation modules, networks, and HTML reporting: EchoGO::echogo_quickstart( run_demo = TRUE, full = TRUE ) Documentation The release includes updated documentation for: running the EchoGO workflow; interpreting consensus results, RRvGO outputs, and GO-term networks; preparing reference-based RNA-seq inputs; installing EchoGO with registered package vignettes. See NEWS.md for the complete technical changelog.

Authors 4

1. Camilo Escobar-Sierra Aachen Institute for Environmental Research

   RWTH Aachen University

   Affiliation as printed

   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 Institute for Environmental Research

   University of Gothenburg · RWTH Aachen University

   Affiliation as printed

   Institute for Environmental Research, RWTH Aachen University, Aachen, Germany; Department of Biological and Environmental Science, University of Gothenburg, Gothenburg, Sweden