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Manual

In class-based targeted assays, the natural M+2 isotopologue of a lighter species can fall in the transition window of a species two mass units heavier and inflate its measured area. MRMhub corrects this with the LICAR method (Gao et al. 2021): for each affected (target) feature it subtracts a fixed fraction K of the interference source’s area, where K is the source’s theoretical M+2 abundance. This is a Type II correction (overlap between different species); Type I natural-abundance (MID) correction of a compound’s own isotopes is not performed.

For MRM data the factor is computed at the fragment, not the whole molecule. Whether the heavy isotope ends up on the product ion or on the neutral loss changes K, so a whole-molecule (MS1) factor does not give the right value for a fragment transition. Class-based LC-MRM therefore uses level = "MRM"; level = "MS1" is reserved for genuine full-scan data and is not a fallback when a product m/z is missing.

The Isotopic interference correction tutorial gives the step-by-step workflow; this page is the concept and label reference.

The mrm_pattern annotation

Automatic derivation needs one hand-added column, mrm_pattern, in the Features sheet of the metadata workbook. It names the lipid class and the product-ion type, from which calc_isotopic_interferences() builds the fragment formula; the precursor and product m/z and the polarity come from the imported data or the metadata. Feature names are parsed with rgoslin, so the usual lipid shorthand is accepted; fatty-acyl (FA) and sphingoid-base (LCB) patterns additionally need a chain-resolved name (PC 16:0_18:1, Cer 18:1;O2/16:0), while a sum-composition name (PC 34:1) suffices for head-group patterns.

The mrm_pattern column in the Features metadata sheet (other feature columns omitted; values illustrative).
feature_id feature_class precursor_mz product_mz polarity mrm_pattern
PC 34:1 PC 760.6 184.1 Pos PC (Pos) Pro=184.1
SM 34:1;O2 SM 703.6 184.1 Pos SM (Pos) Pro=184.1
Cer 18:1;O2/16:0 Cer 538.5 264.3 Pos Cer (Pos) SphB-2H2O

On import the label is validated: an unknown label is an error, and a label whose class disagrees with the feature name, or a sum-composition name under an FA/LCB pattern, is a warning. The save_metadata_templates() workbook offers the labels as a filtered dropdown.

Most lipidomics assays use a handful of classes: the head-group patterns (PC (Pos) Pro=184.1, SM (Pos) Pro=184.1, LPC (Pos) Pro=184.1, PE (Pos) Pre-Pro=141), the sphingoid-base patterns for ceramides (Cer (Pos) SphB-2H2O, Hex1Cer (Pos) SphB-2H2O), and, in negative mode, the fatty-acyl patterns (PC (Neg, FA) FA, PE (Neg) FA). Not every valid label is auto-derived (see the note below the list). The complete list is at the end of this page.

Derivation levels

calc_isotopic_interferences() discovers the overlaps and stores them in annot_interferences; the level argument selects how K is computed.

level = "MRM" level = "MS1"
Intended data Class-based LC-MRM (precursor and product m/z) Genuine MS1 / full-scan (precursor m/z only)
Correction basis Fragment formula (product ion or neutral loss) Whole-molecule precursor formula
Pairing scope Within an mrm_pattern Within a feature_class
Applies to Lipids (needs the class fragment chemistry) Any compound with a formula

At the MRM level a head-group transition carries a single overlap. A fatty-acyl or sphingoid-base transition can carry two at once: one source whose extra mass sits on the retained product ion, and one on the neutral loss. The correction subtracts both. Each overlap is one row of annot_interferences, with overlap_type m2_head, m2_front, m2_back, or ms1_m2, and source auto (derived) or manual (declared in the metadata). calc_isotopic_interferences() warns when MS1 derivation is run on data whose product m/z differs from the precursor, i.e. real MRM transitions.

Co-elution

The correction subtracts the source’s full area, so it applies only where the interference source and target peaks co-elute and/or are co-integrated. The experimental check_coelution = TRUE enforces this, dropping m/z-matched pairs that are chromatographically resolved. It is off by default while the gate is validated.

Provenance

The factors are theoretical isotope abundances, computed with enviPat 2.8 (Loos et al. 2015). The version is pinned to reproduce the published LICAR values, and calc_isotopic_interferences() warns when a different version is installed. Derivation is deterministic, and the derived annot_interferences table travels with the saved object and the report workbook, so the correction is reproducible from the metadata alone.

mrm_pattern labels

The valid labels follow the original LICAR class list (Gao et al. 2021), grouped by the product-ion type the transition monitors: head group, fatty acyl (FA), and sphingoid base (LCB), which MRMhub extends with neutral-loss and reversed-phase (RPLC) patterns. licar_pattern_choices() returns the same list from R.

Automatic derivation covers the head-group, fatty-acyl (FA), and sphingoid-base (LCB) patterns. Neutral-loss classes (CE, DG, TG) and cardiolipin FA (CL) can be annotated but are not auto-derived at the MRM level: calc_isotopic_interferences() skips them with a warning, and a correction for them must be declared manually with correct_custom_interferences(). The RPLC labels and a few placeholder entries (PC d9, MG) are valid labels but are not offered in the template dropdown.

Next steps

References

Gao, Liang, Shanshan Ji, Bo Burla, Markus R. Wenk, Federico Torta, and Amaury Cazenave-Gassiot. 2021. LICAR: An Application for Isotopic Correction of Targeted Lipidomic Data Acquired with Class-Based Chromatographic Separations Using Multiple Reaction Monitoring.” Analytical Chemistry 93 (6): 3163–71. https://doi.org/10.1021/acs.analchem.0c04565.
Loos, Martin, Christian Gerber, Frederic Corona, Juliane Hollender, and Heinz Singer. 2015. “Nontarget Screening with High-Resolution Mass Spectrometry in the Environment: Ready to Go?” Environmental Science & Technology 49 (3): 1857–65. https://doi.org/10.1021/es5040179.