Coding & Dev Tools

holobiomicslab Skill

Use when you have downloaded and extracted a GNPS archive (from METABOLOMICS-SNETS, METABOLOMICS-SNETS-V2, FEATURE-BASED-MOLECULAR-NETWORKING for GNPS1, or classical_networking_workflow/feature_based_molecular_networking_workflow for GNPS2) and need to construct a queryable molecular family graph.

holobiomicslab Skill

Use when after completing the MS2LDA LDA modeling step when you have a JSON-serialized inferred motifset (Mass2Motifs with fragment and neutral-loss patterns) and need to annotate those motifs by comparing them against a curated MotifDB reference database to identify known structural subpatterns.

holobiomicslab Skill

Use when when you have vendor-format GC-CI-MS or LC-MS data from stable isotope labeling experiments, a target list of compounds with known monoisotopic m/z, retention time, and elemental formula, and you need per-isotopologue area and intensity values for quantification or downstream statistical.

holobiomicslab Skill

Use when when you have initialized an MsBackend subclass (e.

holobiomicslab Skill

Use when you have two or more nontargeted LCMS feature tables from the same analytical method and need to establish matched feature correspondences across datasets, then consolidate redundant features.

holobiomicslab Skill

Use when you have processed LC-MS run data (feature table or peak detection output) containing internal standard identifications with retention times, m/z values, and intensity measurements across multiple samples, and you need to rapidly detect instrumental drift, retention time shifts, or.

holobiomicslab Skill

Use when when you have computed Spec2Vec similarity scores (typically cosine similarity in [0, 1] range) between discovered Mass2Motifs and a spectral library, and need to decide which matches are sufficiently confident to include in per-motif annotation output.

holobiomicslab Skill

Use when after auto-deconvolution of GC-MS data has produced a table of individual deconvolved mass spectra (one per detected peak), and your goal is to group spectra into molecular families based on mass spectral similarity rather than retention time or chemical class.

holobiomicslab Skill

Use when before attempting to run QCxMS2 for the first time, after updating any external dependencies (xtb, CREST, molbar, orca, geodesic_interpolate), or when troubleshooting unexplained calculation failures.

holobiomicslab Skill

Use when when working with raw or filtered MsmsSpectrum objects where peak intensities span a wide dynamic range and need to be normalized for downstream spectrum comparison, database matching, or publication-quality visualization.

holobiomicslab Skill

Use when you have loaded a raw or partially processed MsmsSpectrum object and need to reduce spectral noise before annotation, matching, or visualization. Use it especially when spectra contain many weak peaks (e.

holobiomicslab Skill

Use when after filtering LC-MS features by statistical significance (e.g., p-value < 0.01) and you wish to group features that represent the same metabolite at different isotopologue states.

holobiomicslab Skill

Use when you have computationally generated precursor m/z values, fragment m/z values, collision energies, and retention time predictions for a set of lipid targets (e.

holobiomicslab Skill

Use when you have a large collection of MS/MS spectra (hundreds of thousands to millions) that need to be clustered, you have already constructed nearest neighbor indexes on low-dimensional spectrum vectors (via feature hashing), and you need to compute only the relevant pairwise distances between.

holobiomicslab Skill

Use when you have executed batch searches of MS/MS spectra against multiple domain-specific MASST indices and need to integrate the resulting match outputs into a single coherent view.

holobiomicslab Skill

Use when after MS1 extraction (coarse/fine error correction, EIC window extraction) and retention time windowing on a set of mzML files tagged with ionization mode and compound adducts.

holobiomicslab Skill

Use when you have raw arrival-time data from TWIM-MS and need to convert it to collision cross section (CCS) values for multi-omic analysis.

holobiomicslab Skill

Use when when integrating an R package that wraps a compiled .NET assembly (such as rawrr), you need to verify that the internal dispatch mechanism between the R layer and the C# layer is operational before attempting to read actual raw data files.

holobiomicslab Skill

Use when you have raw mass spectrometry intensity data from targeted analytes and a set of calibration standard measurements with known concentrations.

holobiomicslab Skill

Use when when you have sum-normalized peak-abundance matrices from FT-ICR MS data with assigned molecular formulas and need to compare metabolite diversity between treatment groups (e.g., inoculated vs. control samples).

holobiomicslab Skill

Use when processing raw MS intensity tables from long measurement sequences where you observe systematic, time-dependent changes in signal magnitude (e.g., progressive increase or decrease in peak intensity across a run).

holobiomicslab Skill

Use when when claiming that one mass spectrometry processing library achieves higher throughput than competitors, or when evaluating whether a new or optimized implementation delivers the expected computational efficiency gains.

holobiomicslab Skill

Use when after loading a raw metabolite abundance table (rows=metabolites, columns=samples) from Metabolomics Workbench format and before mapping metabolites to pathway identifiers or computing enrichment statistics.

holobiomicslab Skill

Use when you have raw MS intensity data paired with known-concentration calibration standard measurements, and you need to convert intensities to absolute or relative concentrations.

holobiomicslab Skill

Use when you need to evaluate whether a newly released or candidate library (e.g., spectrum_utils v0.4.

holobiomicslab Skill

Use when when implementing or extending a DSL parser (lexer + recursive descent or LALR parser) that accepts user-authored query strings.

holobiomicslab Skill

Use when you have a preprocessed peak table (feature matrix with samples × peaks), known sample class labels or group membership, and a goal to classify or discriminate between two or more sample groups.

holobiomicslab Skill

Use when you have raw MS intensity tables showing systematic drift during a measurement sequence (e.g., declining or variable ion counts across a run), particularly in targeted quantification workflows where external calibration standards are available.

holobiomicslab Skill

Use when when implementing or initializing an MsBackend subclass to handle mass spectrometry data, you must assign dataStorage and dataOrigin variables after loading m/z and intensity values.

holobiomicslab Skill

Use when you have 512-dimensional representation vectors output from paired ResNet18 encoders processing augmented ion images, and you need to: (1) introduce an intermediate projection space to enable contrastive loss optimization without trivial/collapsed solutions, (2) further compress learned.

holobiomicslab Skill

Use when when you have native metabolite structures (SMILES or mol format) and need to predict adduct ions for a mass spectrometry imaging experiment that uses a derivatizing matrix known to produce ions other than common [M+H]+ (positive mode) or [M-H]- (negative mode).

holobiomicslab Skill

Use when after retention-time-based and abundance-correlation-based feature grouping have produced composite feature groups, and you need to identify which features within a group actually represent different compounds.

holobiomicslab Skill

Use when after feature detection has produced a TSV feature table (from Asari or equivalent) containing m/z, retention time, and intensity columns, and before MS1 or MS2 annotation.

holobiomicslab Skill

Use when after executing MassQL queries against a MotifDB reference database and retrieving ranked motif matches, when you need to determine which database entries represent true structural correspondence versus spurious matches, and to decide whether a motif's top-ranking hit is sufficiently.

holobiomicslab Skill

Use when you are extending the MsBackend virtual class to create a new backend for storing MS spectra data and need to define the internal data structure. Specifically: when you have multiple types of spectra variables (e.

holobiomicslab Skill

Use when after you have identified statistically significant LC-MS features and run MamsiStructSearch to generate structural clusters (isotopologue groups, adduct groups, cross-assay links) and computed correlation cluster assignments.