# Dda Mode Metabolomics Data Processing > Use when when you have LC-MS/MS data collected in DDA mode and suspect that MS/MS spectra contain chimeric (multiply-charged or co-fragmented) ion signals that will degrade downstream spectral matching, library searching, or metabolite identification. - Skill: `holobiomicslab/dda-mode-metabolomics-data-processing-2` (Agent Skill) - Install (CLI): `npx skillmds@latest add holobiomicslab/dda-mode-metabolomics-data-processing-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/holobiomicslab/dda-mode-metabolomics-data-processing-2/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - License: CC-BY-4.0 - Author: HolobiomicsLab (https://skillmd.com/u/holobiomicslab) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/holobiomicslab/dda-mode-metabolomics-data-processing-2 --- # dda-mode-metabolomics-data-processing > **License: restricted** — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution. ## Summary Purify chimeric MS/MS spectra from untargeted metabolomics data acquired in Data-Dependent Acquisition (DDA) mode using DNMS2Purifier, a bioinformatic solution that removes or flags co-fragmented ion signals that confound spectral interpretation and compound identification. ## When to use When you have LC-MS/MS data collected in DDA mode and suspect that MS/MS spectra contain chimeric (multiply-charged or co-fragmented) ion signals that will degrade downstream spectral matching, library searching, or metabolite identification. This is particularly critical for untargeted metabolomics workflows where spectral purity directly impacts annotation confidence. ## When NOT to use - Input data is already a feature table or quantified metabolite matrix (run purification before feature extraction, not after). - Data were acquired in targeted or parallel reaction monitoring (PRM/SRM) mode rather than untargeted DDA (DNMS2Purifier is specific to DDA mode). - Raw spectra have already been deconvoluted or processed by another chimeric-spectrum removal tool (applying DNMS2Purifier to pre-filtered spectra may introduce redundant filtering or bias). ## Inputs - LC-MS/MS raw data files acquired in Data-Dependent Acquisition (DDA) mode - Precursor and fragment m/z lists with intensity values - Scan metadata (retention time, precursor charge, isolation window) ## Outputs - Purified MS/MS spectra with chimeric signals removed or flagged - Annotated spectrum quality metrics (chimeric score or confidence) - Filtered spectral library or feature table suitable for downstream matching ## How to apply Obtain the DNMS2Purifier.r script from the HuanLab GitHub repository and confirm R 4.2.1 is installed with required dependencies available. Load the script and parse its function definitions to verify MS/MS purification logic and chimeric spectrum filtering routines are syntactically sound. Execute DNMS2Purifier.r on your DDA-mode LC-MS/MS data (typically in a format accepted by the script, such as mzML or vendor-specific formats). The program applies machine-learning or heuristic-based chimeric spectrum detection to identify and flag MS/MS scans containing multiple precursor ions or co-fragmented species. Validate the output spectra are properly formatted and that chimeric MS/MS signals have been successfully removed or annotated; cross-check purified spectra against raw data to confirm filtering logic did not remove genuine singleton spectra. ## Related tools - **DNMS2Purifier.r** (Main R script for executing MS/MS spectrum purification on DDA-mode LC-MS/MS data; detects and filters chimeric MS/MS spectra) — https://github.com/HuanLab/DNMS2Purifier - **DNMS2Purifier_model_generation.r** (R script for training customized chimeric spectrum detection models tailored to specific instrument or ionization method configurations) — https://github.com/HuanLab/DNMS2Purifier - **R** (Execution environment and scripting language required to run DNMS2Purifier (version 4.2.1)) ## Examples ``` Rscript DNMS2Purifier.r --input raw_dda_spectra.mzML --output purified_spectra.mzML ``` ## Evaluation signals - Output spectra conform to expected format (e.g., mzML, or the format native to the input); no malformed or truncated records. - Chimeric spectra are correctly identified and tagged: spot-check flagged spectra to confirm they contain multiple precursor m/z peaks or fragments inconsistent with a single molecular ion. - Singleton (non-chimeric) spectra are preserved in output: comparison of spectrum count between input and output should show only expected loss; manual inspection of a subset confirms genuine spectra were not over-filtered. - Purified spectra show improved match scores in downstream spectral library searching compared to raw spectra, indicating reduced noise from co-fragmented ions. - Reproducibility check: re-running DNMS2Purifier.r on the same input produces identical or equivalent output (no stochastic variation if model is fixed). ## Limitations - DNMS2Purifier is optimized for DDA mode; applicability to other acquisition modes (PRM, SRM, data-independent acquisition) is not established in the provided documentation. - No changelog or version history is available in the source repositories, making it difficult to track bug fixes or feature improvements across releases. - Model performance is dependent on training data and instrument/ionization method; users may need to generate customized models via DNMS2Purifier_model_generation.r for non-standard configurations. - Computational cost and runtime are not explicitly characterized in the provided documentation; performance on very large LC-MS/MS datasets is unknown. ## Evidence - [readme] DNMS2Purifier is a bioinformatic solution that purifies chimeric MS/MS spectra from LC-MS/MS-based untargeted metabolomics in Data-Dependent Acquisition (DDA) mode.: "DNMS2Purifier is a bioinformatic solution that purifies chimeric MS/MS spectra from LC-MS/MS-based untargeted metabolomics in Data-Dependent Acquisition (DDA) mode." - [readme] The R script DNMS2Purifier.r is the main program for MS/MS purification, we also provide the script DNMS2Purifier_model_generation.r for customized model training: "The R script DNMS2Purifier.r is the main program for MS/MS purification, we also provide the script DNMS2Purifier_model_generation.r for customized model training" - [readme] The program is written in R (ver 4.2.1).: "The program is written in R (ver 4.2.1)." - [intro] DNMS2Purifier.r serves as the main program that purifies chimeric MS/MS spectra from LC-MS/MS-based untargeted metabolomics data acquired in Data-Dependent Acquisition (DDA) mode.: "DNMS2Purifier.r serves as the main program that purifies chimeric MS/MS spectra from LC-MS/MS-based untargeted metabolomics data acquired in Data-Dependent Acquisition (DDA) mode." - [other] Validate that the output spectra are properly formatted and chimeric MS/MS signals have been successfully removed or flagged.: "Validate that the output spectra are properly formatted and chimeric MS/MS signals have been successfully removed or flagged."