EchoGO: A Cross-Species Consensus Framework for Functional Enrichment in Non-Model Organisms

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.

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