Raw Data Naming Conventions for Peptide LC-MS Records

Principles and objectives

Naming conventions for peptide LC‑MS raw data should prioritize unambiguous identification, machine readability, and compatibility with downstream archive or repository workflows. The goal is to enable reproducible analysis, rapid retrieval, and straightforward mapping between raw files, sample metadata, and processed outputs. Adopt a consistent, documented scheme at project outset and apply it across instrument platforms, conversion outputs (e.g., vendor raw, mzML), and backups.

Core filename elements

Construct filenames from a limited set of atomic elements separated by a single delimiter such as underscore (_) or hyphen (-). Recommended elements include:

• Project or study code (short and unique)
• Sample identifier (unique within the project)
• Prep or fraction identifier (if applicable)
• Instrument identifier (make/model or lab code)
• Acquisition date in ISO format YYYYMMDD
• Run sequence or injection number (zero-padded)
• File type or conversion suffix (RAW, mzML, mzXML)

Example token order: Project_Sample_Fraction_Instrument_YYYYMMDD_Injection.FileExt

Formatting rules and best practices

Adopt deterministic and parsable formatting rules to avoid ambiguity:

• Use ISO dates (YYYYMMDD) to keep lexical sort = chronological sort.
• Pad numeric fields (e.g., 01, 02) for consistent sorting and parsing.
• Avoid spaces and special characters; restrict to A–Z, a–z, 0–9, hyphen, and underscore.
• Keep tokens short but descriptive; document any abbreviations in a simple key file stored with the dataset.
• Include file extension that reflects the format (e.g., .RAW, .mzML) so tools and archives can recognize type at a glance.

Examples and patterns

Below are example patterns illustrating how to combine core elements. These are patterns, not prescriptive templates — adapt to local needs while preserving the stated principles.

• Single-injection peptide run: PROJ01_SMP012_F01_QExactive_20260615_01.RAW
• Converted open format: PROJ01_SMP012_F01_QExactive_20260615_01.mzML
• Fractionated set: PROJ01_SMP012_F02_QExactive_20260617_03.mzML

When programmatically parsing names, use regular expressions that reference documented token positions rather than attempting to infer meaning from variable-length tokens.

Versioning, checksum, and storage mapping

Track processed derivatives and conversions by appending a version or tool tag (e.g., _v1, _mzMLconv2026) while preserving the original acquisition tokens. Store checksums (SHA256) adjacent to files in a manifest (manifest.csv or manifest.md5) to verify integrity during transfers and long-term archiving.

Organize storage hierarchically for performance and clarity. Example path layout:

/archive/PROJ01/2026/06/SMP012/PROJ01_SMP012_F01_QExactive_20260615_01.mzML

Maintain a separate metadata table (CSV or JSON) linking filename to controlled vocabulary fields such as sample source, preparation protocol ID, and instrument method reference. Maintain the mapping as authoritative for downstream analyses.

Integration with public repositories and standards

When preparing datasets for repository submission, map local tokens to repository metadata fields rather than embedding excessive metadata into filenames. Public repositories and community formats provide structured metadata mechanisms; for guidance on accepted file formats and repository expectations, consult repository documentation such as the PRIDE file formats overview (PRIDE file formats).

For institutional data management practices and recommended naming principles, see guidance such as the Harvard Data Management file naming conventions (Harvard file-naming conventions).

Governance and documentation

Document the chosen convention in a short README that accompanies the dataset, including example filenames, token definitions, and parsing regular expressions. Apply controlled change management for any schema updates and provide a migration mapping for legacy files.

Consistent, well-documented naming conventions reduce ambiguity, speed data discovery, and simplify automated processing pipelines used by qualified laboratory researchers handling peptide LC‑MS raw data.

Not for human consumption. For laboratory research use only.