Version Control for Peptide Data Analysis: Reproducing a Published Figure

A peptide research figure can become difficult to reproduce when its script, input file, and analysis settings were edited after the image was exported. Version control helps preserve the sequence of changes, but a complete analysis record must also connect the code to the data and environment used for each result.

The practical goal is straightforward: another analyst should be able to identify the exact inputs and decisions behind a reported number or figure.

Separate original observations from derived outputs

Keep instrument exports or other original data distinct from processed tables, summaries, and presentation graphics. Preserve a record of how each derived file was produced.

For a hypothetical assay analysis, a cleaned table should not silently replace the original export. If a row was corrected or excluded, the transformation should be visible in a script or a documented change record.

Assign stable identifiers to experiments and files. A descriptive filename can help a person navigate, but it should not be the only link between a plotted point and its source measurement.

Use commits to record meaningful changes

Git's official guide to recording changes explains tracked files, staging, and committed snapshots. For research analysis, a useful commit groups a coherent change and explains why it was made.

Examples include correcting a unit conversion, changing a documented exclusion rule, or updating a plotting script. The message should describe the analytical consequence, not merely say that the file was updated.

Version control only preserves content that is actually included in its history. A local uncommitted adjustment can still create a figure that differs from the recorded analysis version.

Record settings and software dependencies

An unchanged script can produce different behavior if its settings or software environment change. Preserve the relevant settings, dependency versions, and instructions needed to run the analysis.

The Carpentries' research computing lessons include version control and reproducible analysis skills. These provide a foundation; the laboratory still needs a workflow suited to its instruments, file types, and data-access requirements.

For a hypothetical fitting workflow, retain the model choice, parameter constraints, and analysis window in a settings file or equivalent record. Those decisions should not exist only in an analyst's memory or an unnamed dialog state.

Link a figure to a specific analysis state

Associate each final figure with the input dataset version, code revision, settings, and run output. Keep a short record of the command or procedure used to generate it.

If large data files are stored outside the code repository, retain their location, access requirements, and an appropriate integrity identifier. A file checksum can help detect changed bytes, although it does not establish that the underlying measurement was scientifically correct.

Test reconstruction from the documented inputs rather than from an analyst's existing working session. Hidden local files and manual steps often become visible only when someone follows the recorded process independently.

Explain revisions without erasing the earlier result

When an analysis changes, state what changed and which conclusions were affected. Preserve earlier versions so a reviewer can distinguish a corrected error from a new methodological choice.

A hypothetical revision might change the displayed uncertainty while leaving the central estimate similar. The report should describe that consequence clearly rather than replacing the figure with no explanation.

Material identity remains part of the data record. Use the site's peptide identifier guide to distinguish the chemical item from internal sample and analysis identifiers, and contact the team for available product records.

Version control supports an auditable analysis history. Scientific reproducibility also depends on preserving the relevant observations, experimental context, and reasoning behind the analysis choices.

Related reading

Continue with Z-Prime Factor in Peptide Screening: What the Assay Window Tells You; BLAST for Short Peptide Sequences: Interpreting Similarity Results; Preregistration for In Vitro Peptide Studies: Writing an Analysis Plan.

For in vitro laboratory research use only. Not for human or animal use or consumption. Not for diagnostic or therapeutic use.