HolobiomicsLab Targeted LC-MS Quantification (calibration -> absolute concentrations)
Summary
Targeted transitions in, a QC'd quantification table out: peak integration, calibration-curve fitting, internal-standard normalization, and batch QC.
When to use
Use when you have targeted LC-MS data for a defined panel of analytes and want absolute or relative concentrations — extract and integrate the target transitions/ion chromatograms, build calibration curves from standards with internal-standard normalization, apply them to samples, and QC the batch (response drift, QC-sample RSD) to a reportable quantification table.
When NOT to use
- The data is not LC-MS.
- You need a single atomic step, not the full pipeline (use the leaf skill directly via the router).
Stages
Stage 1 — integrate
Goal: raw targeted LC-MS -> integrated peak areas for target transitions
EDAM operation: operation_3215
Inputs: mzML · Outputs: feature-table
Candidate leaf skills: targeted-peak-detection-and-integration (primary), chromatographic-peak-detection-and-integration, targeted-peak-detection-screening-and-validation, targeted-peak-extraction-ms1, m-z-and-retention-time-window-validation
Tools (primary): TARDIS, Spectra, R, MSConvert (ProteoWizard), xcms, MsExperiment
Other candidate tools: knitr, kableExtra, ProteoWizard MSConvert, IonToolPack, PeakQuant, PeakQC, Comparador
Grounding: 2 KB(s); DOIs: 10.1021/acs.analchem.5c00567, 10.1021/jasms.4c00146
Stage 2 — calibrate
Goal: calibrant standards -> calibration curves with internal-standard normalization
EDAM operation: operation_3435
Inputs: feature-table · Outputs: tsv
Candidate leaf skills: calibration-curve-fitting-metabolomics (primary), calibration-curve-validation, linear-regression-concentration-calibration, linear-regression-model-fitting
Tools (primary): R, mzQuality, SummarizedExperiment, mzQualityDashboard, R (lm, weighted.lm)
Other candidate tools: Shiny, QuantyFey, GetFeatistics, lme4, AER, R base, Python 3, networkx, mass2chem, khipu, RawFileReader, rawrr, R base stats package (lm function)
Grounding: 6 KB(s); DOIs: 10.1016/j.aca.2025.344571, 10.1021/acs.analchem.2c05810, 10.1021/acs.jproteome.0c00866, 10.1021/jasms.5c00073 …
Stage 3 — quantify
Goal: apply calibration -> absolute / relative concentrations per sample
EDAM operation: operation_3799
Inputs: feature-table, tsv · Outputs: tsv
Candidate leaf skills: concentration-prediction-from-calibration-model (primary), linear-regression-absolute-quantification, concentration-prediction-from-calibration-curves
Tools (primary): R, mzQuality, SummarizedExperiment, mzQualityDashboard
Other candidate tools: GetFeatistics, lme4, AER
Grounding: 2 KB(s); DOIs: 10.1021/jasms.5c00073, 10.1515/jib-2025-0047
Stage 4 — qc [OPTIONAL]
Goal: (optional) batch QC — response drift, QC-sample RSD, outlier flagging
EDAM operation: operation_3435
Inputs: tsv · Outputs: tsv
Candidate leaf skills: qc-sample-variability-assessment (primary), qc-sample-reliability-evaluation, qc-sample-batch-drift-correction, batch-effect-assessment-via-quality-metrics, signal-trend-assessment-across-injections
Tools (primary): R, mzQuality, SummarizedExperiment, mzQualityDashboard
Other candidate tools: notame, Biobase, MetCorR, OUKS, QComics, Sciex Multiquant
Grounding: 5 KB(s); DOIs: 10.1021/acs.analchem.3c03660, 10.1021/acs.jproteome.1c00392, 10.1021/jasms.5c00073, 10.1093/bioinformatics/btr597 …
Stage 5 — report
Goal: consolidate concentrations + QC into a reportable quantification table
EDAM operation: operation_3434
Inputs: tsv · Outputs: tsv
Candidate leaf skills: quality-control-report-generation (primary), quality-control-metric-threshold-configuration, quality-control-metric-computation, qc-summary-table-extraction, compound-metric-tabulation
Tools (primary): R, mzQuality, SummarizedExperiment, mzQualityDashboard
Other candidate tools: R ≥4.1.2, OUKS step 4 (Correction.R), OUKS step 6 (Filtering.R), ggplot, data.table, mpactr, ggplot2
Grounding: 4 KB(s); DOIs: 10.1021/acs.analchem.2c04632, 10.1021/acs.jproteome.1c00392, 10.1021/jasms.5c00073, 10.1128/mra.00997-24
Grounding
Each stage carries the kb_slugs/dois of the leaves it draws on. Ground any stage against its source paper with the collection's /ground command or bin/perspicacite_kb_bind.py (Perspicacité KB; serverless local-clone fallback).
Verification contract
workflow.yaml is gradable by asb solve-workflow (checkpoint mode). Each stage declares typed outputs; the final stage emits the master deliverable.
Provenance
Generated by compose_workflows.py (semantic binding + EDAM-aware primary selection). derived_from_workflows lists ASB per-paper workflows whose structure corroborated this pipeline — the eval-ablation set (SPEC §8). Staging only; promote via release_gate.py.