Coding & Dev Tools

holobiomicslab Skill

Use when you have millions of MS/MS spectra in mzML, mzXML, or MGF format that have been converted to low-dimensional vectors via feature hashing, and you need to identify which spectra are similar enough to cluster together.

holobiomicslab Skill

Use when when you have reimplemented an algorithm in a new package or optimized an existing algorithm and need to verify that the new version produces the same numerical results as the original or reference implementation.

holobiomicslab Skill

Use when you have raw metabolomic LC-MS data processed through XCMS CentWave feature extraction and want to improve true positive feature recovery while controlling false positive rate and crash likelihood.

holobiomicslab Skill

Use when you have picked peaks (coordinates and intensities) from INADEQUATE spectra and need to distinguish which peaks likely originate from the same metabolite before matching to a reference database.

holobiomicslab Skill

Use when after loading feature identification results (e.g., from OpenSwath or other DIA search engines) when you need to display only confident peptide precursors and their chromatograms.

holobiomicslab Skill

Use when you have a feature intensity matrix (peak vector) and a corresponding set of QC sample indices from a multi-batch LC/GC-MS experiment, and you need to establish batch-invariant reference statistics before applying QC-based batch correction methods such as bcpareto(), bccenter(), or.

holobiomicslab Skill

Use when when importing a new batch of centroided mzML or mzXML LC-MS files into MetCohort, before any data alignment or feature detection is performed. At least one file must be designated as QC to enable ROA detection and alignment;

holobiomicslab Skill

Use when you have computed RAS (Reaction Activity Scores) from transcriptomics and GPR rules, RPS (Reaction Propensity Scores) from intracellular metabolomics via mass-action kinetics, and flux distribution differences (FFD) from constraint-based sampling across multiple biological samples.

holobiomicslab Skill

Use when you have preprocessed, statistically significant LC-MS features (from multiple assays or a single assay) and need to group features that represent the same metabolite in different isotopic labeling states.

holobiomicslab Skill

Use when you have completed the MS2LDA LDA modeling phase and possess motifset.json or motifset_optimized.json files containing inferred Mass2Motifs.

holobiomicslab Skill

Use when you have a feature list from LC- or GC-HRMS analysis (with m/z, retention time, and exact mass columns) and you want to detect homologous series of PFAS compounds that repeat by CF₂ mass increments (typically ≈34 Da).

holobiomicslab Skill

Use when you have (1) genomic data from a Streptomyces or other RiPP-producing organism in raw FASTA format or annotated GenBank format, (2) high-resolution LC-MS/MS spectra in centroided MGF, mzML, mzXML, or mzData format, and (3) a known or predicted lantibiotic core peptide sequence you wish to.

holobiomicslab Skill

Use when after performing peak detection on centroided .mzML LC-MS data with screening_mode=FALSE in TARDIS.

holobiomicslab Skill

Use when after ISFrag has completed identification of in-source fragment features (Part 4 output), when you need to serialize and inspect the hierarchical fragmentation relationships among identified ISF features, or when preparing data for visualization or external analysis of fragment lineage and.

holobiomicslab Skill

Use when you have two or more mass spectral libraries in different formats (NIST binary exports converted to MSP, MoNA downloads, RIKEN public databases, GNPS MGF, or batches of in-house standards in separate MSP files) and need to combine them with consistent metadata (SMILES, InChIKey, molecular.

holobiomicslab Skill

Use when you have mwTab-formatted files from the Metabolomics Workbench containing MS or NMR experimental metadata and tabular data sections (e.g., METABOLITES, DATA blocks), and need to load them into memory for downstream conversion, validation, or analysis rather than manual text parsing.

holobiomicslab Skill

Use when you have centroided MS2 spectra from data-dependent LC- or GC-HRMS measurements and need to rapidly prioritize potential PFAS features within a larger feature set.

holobiomicslab Skill

Use when when you have Thermo Fisher Scientific .raw files from Orbitrap instruments and need to build a quantitative summary of MS1 acquisition intensity dynamics across a run—specifically, the m/z and intensity of the most intense peak in each MS1 scan.

holobiomicslab Skill

Use when when implementing adduct detection in LC-MS metabolomics workflows, after defining theoretical adduct mass offsets (e.g., [M+NH4]+ at +17.0266 Da, [M+K]+ at +38.9815 Da), and before assigning adduct labels to a feature table.

holobiomicslab Skill

Use when you have two peak-picked, conventionally aligned untargeted LC-MS metabolomics datasets (metabData objects) acquired under different conditions and need to identify overlapping <m/z, retention time> features across them.

holobiomicslab Skill

Use when you have normalized abundance data from LC-MS/MS for multiple samples classified into three or more discrete groups (e.

holobiomicslab Skill

Use when your input is a SummarizedExperiment containing multiple batches or injection sequences of metabolomics samples (study samples, QC replicates, calibration lines) with measured ion areas for compounds and assigned internal standards.

holobiomicslab Skill

Use when when you have multi-batch metabolomics data (SummarizedExperiment object with raw or log-transformed assays) and need to assess whether specific metabolites exhibit systematic signal drift across experimental run order or strong batch effects that would justify hierarchical normalisation.

holobiomicslab Skill

Use when you have raw untargeted LC/MS data in open mzML or mzXML format and need to extract a quantified feature matrix (m/z and retention time coordinates with sample intensities) without prior knowledge of optimal signal detection parameters, batch effects, or quality control samples.

holobiomicslab Skill

Use when you have raw LC-MS data in mzML or equivalent binary format from a public repository (MetaboLights, MassIVE) or instrument vendor output, and need to ingest it into MetaboAnalystR 4.0 for unified LC-MS1 feature detection and MS/MS spectra processing.

holobiomicslab Skill

Use when you have a Sciex Multiquant (≥v3.0.3) txt export containing QCpool sample measurements at multiple timepoints within a sequence, and you need to flag compounds with high technical variability or signal degradation before proceeding to statistical analysis or interpretation of.

holobiomicslab Skill

Use when you have raw tabular experimental metadata (mass spectrometry or NMR sample descriptions, sample-to-treatment mappings, instrument parameters, etc.) that needs to be deposited into a structured online repository like Metabolomics Workbench, but the raw format does not conform to the.

holobiomicslab Skill

Use when apply fillPeaks after retention time alignment (whether XCMS or ncGTW) when feature matrices contain missing peaks across samples due to alignment gaps or detection failures.

holobiomicslab Skill

Use when you have natural product molecules (or compounds from natural product-like databases such as COCONUT or ZINC) in structural format (SMILES, InChI, or SDF file) and need a fingerprint representation optimized for biosynthetic-class prediction, structural clustering, or bioinformatic feature.

holobiomicslab Skill

Use when when evaluating or designing a mass spectrometry data analysis platform, and you need to verify that every supported separation/ionisation technique (LC, GC, IMS, MS Imaging) is covered by at least one processing module.

holobiomicslab Skill

Use when you have LC-MS/MS data in mzML, mzXML, or MGF format from one or more metabolomics samples and need to compare samples that may have poor overlap in detected features, strong retention time shifts between runs, or were acquired on different LC methods or MS technologies (e.

holobiomicslab Skill

Use when you have a collection of MS/MS spectra in standard formats (mzML, MGF) and need to perform rapid similarity search, clustering, or joint analysis across millions of spectra without repeated peptide database searches.

holobiomicslab Skill

Use when when you have mass spectral libraries from multiple sources (NIST, MoNA, RIKEN, GNPS) in disparate formats (MSP, MGF, MOL folder structures) or with misaligned metadata (e.

holobiomicslab Skill

Use when after harmonizing MS/MS spectra and metadata fields (compound identifiers, adduct annotations, collision energies, instrument types) to a common schema, and before exporting the spectral library to standardized formats (mzML, mzTab, or repository-native format).

holobiomicslab Skill

Use when you have a collection of preprocessed and cleaned mass spectrometry spectra (in mzML, mzXML, msp, MGF, or JSON format) and need to compute all-pairs or targeted spectral similarity scores to identify related spectra, perform spectral library searches, or build a similarity network.

holobiomicslab Skill

Use when you have a directory containing mass spectrometry data files from multiple instrument vendors (Thermo, AB Sciex, Agilent, Bruker, etc.) and need to convert them to a common format (Aird or mzML).