SDRF-Proteomics

1. Status of this Template

This document provides a template for annotating Data-dependent acquisition (DDA) mass spectrometry experiments in SDRF-Proteomics format. This template defines additional columns that can be combined with any core template (human, vertebrates, etc.) to capture DDA-specific metadata.

Type: Experiment-type Template (used in combination with core templates)

Status: Released

Version: 1.1.0 - 2026-01

2. Abstract

Data-dependent acquisition (DDA) is the most widely used mass spectrometry acquisition strategy for proteomics. This template captures acquisition-specific parameters that affect data quality and reproducibility: dissociation method, collision energy, fractionation, modification parameters, mass tolerances, and MS2 mass analyzer.

3. Checklist

This section defines the metadata columns required and recommended for DDA experiments.

3.1. Recommended Columns

The following columns are RECOMMENDED for DDA experiments (in addition to the core SDRF-Proteomics requirements):

ColumnRequirementDescriptionOntology/CVExample Values
comment[dissociation method] RECOMMENDED Fragmentation method used PRIDE (MS:1000044) NT=HCD;AC=PRIDE:0000590
comment[modification parameters] RECOMMENDED Post-translational modifications searched UNIMOD NT=Oxidation;MT=Variable;TA=M;AC=UNIMOD:35;PP=Anywhere

3.2. Optional Columns

The following columns are OPTIONAL but commonly used:

ColumnRequirementDescriptionOntology/CVExample Values
comment[collision energy] OPTIONAL Collision energy used for fragmentation PSI-MS (MS:1000045) 27, 30, normalized 27
comment[fractionation method] OPTIONAL Method used to fractionate the sample before MS PRIDE (PRIDE:0000550) NT=High-pH reversed-phase chromatography;AC=PRIDE:0000564
comment[precursor mass tolerance] OPTIONAL Mass tolerance for precursor ions in database search Numeric value with unit 10 ppm, 20 ppm
comment[fragment mass tolerance] OPTIONAL Mass tolerance for fragment ions in database search Numeric value with unit 0.02 Da, 20 ppm
comment[MS2 mass analyzer] OPTIONAL Mass analyzer used for MS2 acquisition PSI-MS (MS:1000443) NT=orbitrap;AC=MS:1000484
Note
 For data file metadata (comment columns), use the full CV term format NT={name};AC={accession} when possible. This format enables automated validation and software can often determine these values from raw files.

4. Example SDRF File

A complete example for a fractionated DDA proteomics experiment:

source name ... assay name comment[proteomics data acquisition method] comment[label] comment[fraction identifier] comment[dissociation method] comment[data file]
liver_sample_001 ... DDA_liver001_F01 Data-dependent acquisition label free sample 1 HCD liver001_F01.raw
liver_sample_001 ... DDA_liver001_F02 Data-dependent acquisition label free sample 2 HCD liver001_F02.raw
liver_sample_002 ... DDA_liver002_F01 Data-dependent acquisition label free sample 1 HCD liver002_F01.raw
Sample metadata Data file metadata
Note
 The …​ column indicates omitted core columns (organism, organism part, disease, biological replicate, technology type, instrument, cleavage agent, modification parameters, etc.).

5. Single-Shot DDA Example

For high-throughput or clinical samples without fractionation:

source name ... assay name comment[proteomics data acquisition method] comment[label] comment[instrument] comment[dissociation method] comment[data file]
plasma_001 ... plasma001_run1 Data-dependent acquisition label free sample Orbitrap Exploris 480 HCD plasma_001.raw
Sample metadata Data file metadata
Note
 For single-shot experiments, comment[fractionation method] can be omitted or set to not applicable.

6. TMT-Labeled DDA Example

For isobaric labeling experiments (TMT, iTRAQ):

source name ... assay name comment[proteomics data acquisition method] comment[label] comment[fraction identifier] comment[dissociation method] comment[data file]
sample_A_rep1 ... TMT_set1_F01 Data-dependent acquisition TMT126 1 HCD TMT_set1_F01.raw
sample_B_rep1 ... TMT_set1_F01 Data-dependent acquisition TMT127N 1 HCD TMT_set1_F01.raw
Sample metadata Data file metadata
Note
 For TMT experiments, multiple samples share the same raw file. Use comment[label] to distinguish channels. TMT quantification can use MS2 or MS3 acquisition—for MS3-based TMT, use PRIDE:0000646 (MS3 spectra).

7. Best Practices for DDA Annotation

  1. Always specify acquisition method: Use comment[proteomics data acquisition method] with Data-dependent acquisition.

  2. Document fragmentation method: Use comment[dissociation method] to specify HCD, CID, ETD, or EThcD—these produce different fragmentation patterns and affect peptide identification.

  3. Include modification parameters: Document all searched PTMs using comment[modification parameters] with UNIMOD accessions.

  4. Document fractionation: Include comment[fractionation method] and properly number fractions with comment[fraction identifier].

  5. Report collision energy: Include comment[collision energy] when available, as it affects fragmentation quality.

  6. Specify MS2 analyzer: Use comment[MS2 mass analyzer] for hybrid instruments (e.g., Orbitrap vs ion trap MS2).

  7. Report mass tolerances when known: comment[precursor mass tolerance] and comment[fragment mass tolerance] aid data reanalysis.

8. Template File

The DDA SDRF template file is available in this directory:

9. Validation

DDA SDRF files should be validated using the sdrf-pipelines tool:

pip install sdrf-pipelines
parse_sdrf validate-sdrf --sdrf_file your_file.sdrf.tsv
Note
 DDA-specific validation rules are under development.

10. Authors and Maintainers

This template was developed by the SDRF-Proteomics community.

For questions or suggestions, please open an issue on the GitHub repository.