Data & Code Availability (pnasnexus-data)

When to trigger

• There is no Data Availability Statement, or it says only "available on request".
• Sequences/structures/datasets are not deposited or have no accession numbers.
• Custom analysis code or scripts are not in a public, archived repository.
• Raw, unprocessed image files have been discarded.
• Unique reagents/strains/cell lines have no sharing plan.

PNAS Nexus's standard (the bar is strict, with teeth)

PNAS Nexus has a mandatory open-data/open-code policy. In the journal's own words:

• "Authors must make all materials, data, and associated protocols, including code and scripts, used in the analysis of the study available to readers in a public repository upon publication."
• "Authors agree to make all data and code used in the analysis of their study fully available upon request during the peer review process or upon publication."
• "All data and any direct outputs from imaging systems must be retained in their raw, unprocessed versions."
• "Failure or refusal to provide data upon request may be grounds for rejection of the manuscript or retraction of the article."

So: public-repository deposition upon publication is required, raw images must be kept, and non-compliance is an explicit rejection/retraction risk. (Confirm the current wording in PNAS Nexus author guidelines.)

Deposit in approved repositories (with accessions)

• Obtain accession numbers / DOIs before/at publication; cite them in the Data Availability Statement and Materials and Methods.
• Code and scripts that produce the results must be public and archived (a versioned release with a citable DOI; a bare GitHub link is not durable).

Cite data and software properly: the [dataset] tag

PNAS Nexus follows the FORCE11 Data Citation Principles and asks authors to flag dataset references with the [dataset] tag in the reference list, so deposited data are formally cited (confirm the exact mechanics in current guidelines). Treat datasets and software as first-class citable objects, not just URLs in the text.

Data & Code Availability Statement (template)

All data and code needed to evaluate the conclusions are present in the paper and/or the Supporting Information and have been deposited in a public repository. [Sequencing data: GEO, accession GSEXXXXXX.] [Structures: PDB, XXXX.] [Analysis code and scripts: Zenodo, DOI 10.5281/zenodo.XXXXXXX.] [Previously published data used here are available at …] [Restricted data (e.g., identifiable human-subjects data) are available from … under … subject to …, in line with the journal's policy.]

Avoid a bare "data available on request" for the primary data behind the figures; restricted human/clinical data must state the access procedure and the controlling body.

Where the statement and the data live

• The Data and Code Availability Statement is a required element of the article (near the end, with the back matter — confirm placement in current guidelines).
• Reference the deposited data in both the availability statement and the Materials and Methods, so a reader following the methods can reach the data.
• Datasets too large for a figure but central to the conclusions go to a repository cited by accession/DOI — not "available on request."

Materials & reagents

• Unique materials (plasmids, cell lines, strains, antibodies) should be available, e.g., via Addgene/repositories or under an MTA; state how.
• Identify key reagents with RRIDs where available.

Ethics & compliance (as applicable)

• Human-subjects: IRB/ethics approval + informed-consent statement.
• Animal work: IACUC/animal-ethics approval and guideline compliance.
• Field/biodiversity: permits and the Nagoya Protocol where relevant.
• Dual-use / biosafety: flag if applicable.

Output format

【Data deposited】 type → repository → accession/DOI (list each) | gaps
【Code/scripts public + archived DOI】 yes/no (link + DOI)
【Raw unprocessed images retained】 yes/no (required)
【Availability statement】 drafted? compliant (public repo on publication; no "on request" only for primary data)?
【[dataset] tags】 data/software cited as first-class objects? yes/no
【Materials sharing】 plan for unique reagents (Addgene/MTA)
【Ethics approvals】 IRB / IACUC / permits present where needed?
【Next】 pnasnexus-significance

Anti-patterns

• Do not write "data available on request" as the only provision for the primary data behind the figures.
• Do not discard raw/unprocessed image files — the policy requires retaining them.
• Do not link only to a personal/lab website (not durable) — use an archival repository with a DOI.
• Do not forget to deposit code and scripts publicly and archive a versioned release.
• Do not treat the data policy as advisory — non-compliance is an explicit rejection/retraction risk.