Data Archiving Overview

JPGR supports open and responsible data sharing to strengthen reproducibility and long term reuse. Authors should deposit datasets in recognized repositories and include a clear data availability statement in the manuscript.

Data archiving improves validation, enables secondary analysis, and increases confidence in molecular findings across proteomics and genomics.

Recommended Repositories

• Proteomics: PRIDE, ProteomeXchange, MassIVE
• Genomics: NCBI GEO, SRA, ENA
• Variant data: dbSNP or ClinVar when applicable
• General repositories: Zenodo, Figshare, Dryad

Minimum Data Package

Authors should provide the data required for independent verification of results. This includes raw data, processed outputs, and metadata describing sample preparation and experimental design.

• Raw instrument or sequencing files
• Processed datasets used for analysis
• Metadata for samples, cohorts, or cell lines
• Quality control summaries and thresholds

File Formats and Metadata

Use standard file formats to improve reuse and interoperability. Provide clear metadata for sample preparation, instrument settings, and bioinformatics pipelines.

Well structured metadata reduces the risk of misinterpretation and supports reanalysis by independent groups.

Proteomics Data Expectations

• Deposit raw spectra and processed outputs where possible
• Include search parameters, software versions, and FDR thresholds
• Provide protein or peptide identification tables
• Describe normalization and batch correction methods

Genomics Data Expectations

• Share raw sequence data or processed variant files when allowed
• Document reference genomes, alignment tools, and filtering criteria
• Provide metadata for sample preparation and sequencing platform
• Clarify quality control thresholds and coverage metrics

Code and Workflow Transparency

Analytical code and workflows improve reproducibility. When feasible, share scripts, pipelines, and container specifications that allow others to reproduce results.

If code cannot be shared, provide sufficient methodological detail to enable independent verification.

Controlled Access and Embargo

For sensitive data, use controlled access repositories and comply with privacy regulations. De identify patient information and ensure consent supports data sharing.

Embargoes may be granted when justified by intellectual property or regulatory requirements, but authors should state the embargo end date and access process.

Citing Datasets

Cite datasets in the reference list and include DOIs or accession numbers. Clear citation supports credit for data generation and helps readers locate supporting evidence.

Data Sharing Workflow

Data Reuse and Accountability

JPGR encourages responsible reuse of datasets with appropriate attribution. Authors should clarify any reuse conditions or licenses linked to the repository record.

If data are reused from public sources, cite the original dataset and describe how it was integrated into the analysis.

Clear reuse documentation improves trust and accelerates secondary analysis by other teams.

Transparent reuse statements also help reviewers evaluate dataset provenance.

Data Archiving FAQ

JPGR Commitment

JPGR is committed to rigorous, transparent publishing in proteomics and genomics. We emphasize reproducible methods, complete data statements, and ethical compliance across all article types.

The editorial office supports authors, editors, and reviewers with clear guidance and responsive communication. For questions about scope or workflow, contact [email protected].

We encourage continuous improvement in reporting practices and share updates that help the community maintain high standards in molecular publishing.