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HolobiomicsLab

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1. ▌
   Mass Accuracy Ppm Filtering · holobiomicslab

   Use when when you have a set of candidate molecular formulae for a measured m/z value and need to rank them by how closely their theoretical m/z matches the observed value.
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   Mass Spectral M Z Alignment · holobiomicslab

   Use when after you have (1) identified putative labelled features with intensity and m/z measurements from LC/MS data (e.g., via basepeak_finder output in geoRge), (2) defined a list of expected ionization adducts (e.
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   Mass Spectrum M Z Alignment · holobiomicslab

   Use when when working with multidimensional MS data (LC–IM–MS/MS) converted to MZA format where spectra are stored in jagged arrays with m/z values distributed across individual HDF5 datasets per scan, and you need to ensure m/z consistency for downstream peak detection, isotope analysis, or.
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   Mass Spectrum Preprocessing · holobiomicslab

   Use when you have raw MS/MS spectra in MGF format with variable peak quality, mixed charge states, or instrument artifacts that could confound clustering or similarity measures.
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   Mass Spectrum Visualization · holobiomicslab

   Use when when you have extracted m/z and intensity arrays from an MZA file (or similar HDF5-backed MS data structure) and need to visually inspect a single MS1 or MS2 spectrum, verify peak characteristics, or diagnose data quality issues before downstream analysis (peak fitting, isotope pattern.
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   Md Defect Ratio Calculation · holobiomicslab

   Use when you have a feature table from LC- or GC-HRMS data (either detected via pyOpenMS or imported as a custom feature list) containing m/z, retention time, and intensity values, and you want to rapidly filter to candidate PFAS features that exhibit the elevated mass defects typical of.
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7. ▌
   Metabolite Feature Flagging · holobiomicslab

   Use when after drift correction and before imputation, when you have a MetaboSet object with LC-MS peak abundances and need to remove features with insufficient detection consistency across QC samples.
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8. ▌
   Metabolite Ms Ms Annotation · holobiomicslab

   Use when when you have SWATH-MS raw data (mzML or vendor format) containing multiplexed MS/MS spectra from multiple co-eluting precursor ions and need to separate these spectra into individual, annotatable component spectra for metabolite identification.
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9. ▌
   Metadata Integrity Checking · holobiomicslab

   Use when after processing LCMS feature data through Blueshift or Gravity but before finalizing results.
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10. ▌
    Model Ablation Study Design · holobiomicslab

    Use when you need to measure how much a specific model capability or architectural feature contributes to prediction performance, especially when that capability is non-obvious or orthogonal to baseline methods.
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11. ▌
    Model Comparison Evaluation · holobiomicslab

    Use when when you have multiple candidate spectrum prediction models (e.g., FFN vs. GNN encoders, NEIMS vs. MassFormer vs. ICEBERG) and need to determine which performs better on a shared task like tandem mass spectrum prediction.
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12. ▌
    Molecular Candidate Ranking · holobiomicslab

    Use when after a trained CNN model has generated molecular embeddings for query spectra, and you need to retrieve the most likely candidate molecules from a reference database.
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13. ▌
    Ms Ms Spectrum Purification · holobiomicslab

    Use when processing LC-MS/MS data acquired in DDA mode that contains chimeric (co-fragmented) MS/MS spectra—i.e., when a single MS/MS scan contains fragments from multiple precursor ions due to co-isolation.
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14. ▌
    Ms2 Spectral Interpretation · holobiomicslab

    Use when you have extracted an MS1 feature table (from XCMS or custom CSV with m/z, retention time, and intensity columns) and one or more DDA mzXML files from the same or related LC-MS runs, and you need to annotate features with MS2 spectral data and match them against a standard spectral library.
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15. ▌
    Multi Module Joint Training · holobiomicslab

    Use when when you have a pretrained encoder that captures domain knowledge (e.g., spectral feature extraction) and need to train task-specific decoder or scoring modules on top of it without degrading the encoder's learned representations.
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16. ▌
    Nextflow Workflow Execution · holobiomicslab

    Use when you have .mzML or .abf LC-HRMS metabolomics raw data files and need to perform peak detection, feature identification, and chromatogram alignment reproducibly across different compute environments (local workstations, HPC clusters).
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17. ▌
    Organism Metadata Retrieval · holobiomicslab

    Use when when a project JSON document contains genome identifiers but lacks corresponding organism name annotations, and you need to link MS/MS mass spectra with genomic context for downstream biosynthetic gene cluster or chemical ecology analysis.
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18. ▌
    Pairwise Matrix Computation · holobiomicslab

    Use when when you have a cleaned MS/MS dataset with chemical structure annotations (SMILES, InChI, or InChIKey) and need to generate ground-truth structural similarity labels for training a deep learning model.
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19. ▌
    Parent Tp Mapping Structure · holobiomicslab

    Use when you have generated a TP object (from generateTPs) with structural information (SMILES) for predicted or library-derived transformation products, and you need to either (1) construct a MetFrag-compatible database that preserves parent compound records alongside TPs, or (2) componentize.
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20. ▌
    Peak Detection In Lcms Data · holobiomicslab

    Use when after retention-time correction has been completed on centroided LC-MS data (mzML or mzXML format) and you need to identify all detected peaks as a unified feature table across a cohort of samples.
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21. ▌
    Peak Table Format Detection · holobiomicslab

    Use when when receiving a peak or feature table output from an unknown or variable upstream peak-picking tool, and you need to route it to the correct ingestion adapter (e.g., in LipidMatch) to normalize and validate it before lipid identification.
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22. ▌
    Pfas Feature Prioritization · holobiomicslab

    Use when you have detected features in LC- or GC-HRMS data (via pyOpenMS or custom feature tables) and need to systematically rank them for likelihood of being PFAS compounds.
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23. ▌
    Project Metadata Validation · holobiomicslab

    Use when when a user uploads a JSON project document to the Pairing Omics Data Platform, before accepting it into the repository or indexing it for search. Use this skill to catch missing required fields, incorrect field types, and constraint violations early in the submission workflow.
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24. ▌
    Pubchem Structure Retrieval · holobiomicslab

    Use when you have an experimental tandem mass spectrum and chemical formula for an unknown compound, and need to identify the true structure among all PubChem entries with that formula.
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25. ▌
    Annotation Scoring And Ranking · holobiomicslab

    Use when you have experimental mass spectra from untargeted metabolomics and need to assign compound identities with confidence estimates.
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26. ▌
    Chemical Shift Data Formatting · holobiomicslab

    Use when you have collected or parsed 1H and 13C NMR peak data (chemical shift values and intensities) and need to submit it to the SMART 3 /api/smart3/search endpoint or similar TensorFlow Serving-backed molecular classification system that expects peaks as JSON rather than raw spectroscopic files.
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27. ▌
    Fragment To Structure Assembly · holobiomicslab

    Use when when you have spectroscopic measurements (1D ¹H or ¹³C NMR) that have been decomposed into predicted substructures or fragments, and you need to reconstruct the full molecular formula and connectivity graph.
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28. ▌
    Inadequate Spectral Processing · holobiomicslab

    Use when you have raw INADEQUATE NMR spectrum files (e.g., in standard NMR formats) that require initial processing before metabolite annotation.
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29. ▌
    Mass Spectral Query Submission · holobiomicslab

    Use when you have one or more individual MS/MS spectra (in mzML, mzXML, or JSON format) and need to identify the compound(s) and their biological source by searching against a domain-specific spectral library.
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30. ▌
    Modification Site Localization · holobiomicslab

    Use when you have a pair of MS/MS spectra—one from a known compound and one from a structurally related modified (unknown) compound—and need to identify which atom(s) in the structure carry the modification.
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31. ▌
    Nmr Modality Ablation Analysis · holobiomicslab

    Use when you have a trained multitask machine learning model for structure prediction, test set molecules with paired ¹H and ¹³C NMR spectra, and need to understand the marginal contribution of each NMR modality or justify multimodal input design.
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32. ▌
    Plasma Serum Sample Comparison · holobiomicslab

    Use when you have NMR-based metabolomics measurements from a cohort containing both plasma and serum samples with associated processing delay metadata (pre- and post-centrifugation times), and you need to determine whether metabolic parameter stability differs between the two sample types or to.
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33. ▌
    R Package Function Integration · holobiomicslab

    Use when you have a published predictive model with known coefficients and feature requirements (e.g., MetaboAge from a peer-reviewed study), a target R package with an established data pipeline (e.
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34. ▌
    Spectral Library Matching Gnps · holobiomicslab

    Use when you have MS2 product-ion spectra in open formats (.mzML or .mzXML) from public mass spectrometry datasets (e.g., from MassIVE with a valid accession) and need to identify chemical compounds by comparing fragmentation patterns against the GNPS reference spectral library.
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35. ▌
    Spectral Mixture Deconvolution · holobiomicslab

    Use when you have an NMR spectrum of a mixture sample and a library of reference spectra for individual compounds, and you need to determine which compounds are present and in what proportions.
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36. ▌
    Spectral Peak Network Grouping · holobiomicslab

    Use when after peak picking has been completed on INADEQUATE NMR spectra and you need to group correlated peaks into compound-specific networks before matching against a metabolite database.
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37. ▌
    Webworker File Access Enabling · holobiomicslab

    Use when you need to run a local HTML file that uses WebWorker or WebAssembly (such as COLMARvista for NMR spectra analysis) and the browser raises cross-origin or file-access policy errors preventing WebWorker initialization or WebAssembly module loading.
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38. ▌
    Cooler File Format Handling · holobiomicslab

    Use when you have a Hi-C dataset stored in cooler format (e.
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39. ▌
    Gc Content Bias Calculation · holobiomicslab

    Use when you have a SummarizedExperiment object containing peak counts from single-cell or bulk ATAC-seq/DNAse-seq data and need to prepare it for unbiased motif deviation analysis.
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40. ▌
    Methylation Data Clustering · holobiomicslab

    Use when after merging methylation call files across all samples into a unified methylBase object (via unite()), when you need to assess whether biological replicates cluster together, identify unexpected sample groupings, or visualize global methylation similarity relationships before proceeding.
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41. ▌
    Motif Peak Overlap Matching · holobiomicslab

    Use when you have a filtered set of non-overlapping peaks from ATAC-seq data and a collection of motifs (typically from JASPAR or similar databases), and you need to identify which peaks contain matches to which motifs as a prerequisite for computing motif-based deviation scores across samples.
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42. ▌
    Simulation Based Validation · holobiomicslab

    Use when when you need to verify that a statistical correction (e.
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43. ▌
    Statistical Test Comparison · holobiomicslab

    Use when when you have run differential methylation analysis in methylKit and need to validate whether overdispersion correction (overdispersion='MN') produces appropriately stringent statistical tests.
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44. ▌
    API Endpoint Communication · holobiomicslab

    Use when you have fingerprint or spectrum data that requires compound-class annotation but prefer not to run SIRIUS locally, or need to integrate predictions into an automated analysis pipeline.
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45. ▌
    Build Status Documentation · holobiomicslab

    Use when when you need to validate that a development build release workflow (such as dev_build_release.yml for a mass spectrometry data processing project) executes without failure and generates artifacts for downstream testing or distribution.
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46. ▌
    Ccs Library Format Parsing · holobiomicslab

    Use when when you have received or cloned a CCS reference library (such as the DTCCSN2 library for U13C labeled lipids) bundled with lipidomics software and need to verify its integrity, understand its lipid class composition, or extract metadata before using it for CCS bias calculation or.
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47. ▌
    CI Status Badge Deployment · holobiomicslab

    Use when you have configured a GitHub Actions workflow that executes build, test, and quality checks, and you want to embed a machine-readable, auto-updating badge in your repository README to signal pipeline status at a glance.
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48. ▌
    Graph Tensor Serialization · holobiomicslab

    Use when after constructing feature tensors encoding atom adjacency matrices, bond types, and chemical properties from canonical SMILES—and before feeding graphs into a GNN training loop—to enable reproducible, portable, and memory-efficient storage of graph objects that will be loaded in batches.
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49. ▌
    Hdf5 Feature Table Loading · holobiomicslab

    Use when you have mass spectrometry feature data stored in HDF5 format (.h5 files) and need to load specific dimensional columns (m/z, drift time, retention time, intensity) for multi-dimensional alignment, CCS calibration, or isotope detection.
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50. ▌
    JSON Directive Application · holobiomicslab

    Use when when you have extracted intermediate JSON conforming to the Experiment Description Specification and need to restructure, filter, sort, or aggregate records (e.
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51. ▌
    Jupyter Notebook Execution · holobiomicslab

    Use when you have access to a published study that provides a Jupyter notebook (.ipynb) containing executable code for reproducing simulations, analyses, or figures, and you need to verify that the reported results can be regenerated in your own environment or adapt the code for a related analysis.
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52. ▌
    Module Import Verification · holobiomicslab

    Use when after installing a Python package (especially one with optional dependencies) to confirm that: (1) core modules are accessible and importable;
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53. ▌
    Mzpeak Format File Parsing · holobiomicslab

    Use when you have an mzPeak file (uncompressed ZIP archive containing Parquet files) and need to extract and work with spectrum metadata (scan descriptions, precursors, selected ions), spectrum signal data (profile or centroid m/z and intensity arrays), or chromatogram data.
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54. ▌
    REST API Endpoint Querying · holobiomicslab

    Use when you have a SMILES string or batch of SMILES strings representing chemical structures and need to obtain NP Classifier predictions programmatically.
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55. ▌
    Richness Index Computation · holobiomicslab

    Use when you have a normalized peak-abundance matrix from FT-ICR MS data (peaks as rows, samples as columns) and need to compare the number and diversity of detected molecular species across experimental conditions—for example, to test whether inoculation or environmental perturbation alters the.
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56. ▌
    S4 Class Method Inspection · holobiomicslab

    Use when you need to verify that an S4 replacement method (e.g., `mz<-`) in a bioinformatics backend class correctly validates input data using vectorized operations on NumericList or similar container objects, rather than inefficient loops or apply functions.
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57. ▌
    Workflow Status Monitoring · holobiomicslab

    Use when you need to verify that a GitHub Actions workflow (such as 'dev_build_release.
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58. ▌
    Batch Design Specification · holobiomicslab

    Use when before applying any batch effect correction function in dbnorm (dbnormPcom, dbnormNPcom, dbnormBer, dbnormBagging, Visodbnorm, or hclustdbnorm), you must first prepare and validate a batch assignment vector that maps each sample to its analytical run or batch.
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59. ▌
    Batch Effect Visualization · holobiomicslab

    Use when you have multi-batch metabolomics data in SummarizedExperiment format and need to demonstrate that batch clustering or run-order signal drift persists in raw/imputed assays but is eliminated after hRUV normalisation (intra-batch loess + RUV-III, followed by inter-batch concatenation).
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60. ▌
    Batch Structure Processing · holobiomicslab

    Use when you have a collection of 100+ molecules in SMILES, SDF, MOL, or MOL2 format and need to compute a unified feature representation combining physicochemical descriptors and structural fingerprints for downstream machine learning.
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61. ▌
    Build Automation Scripting · holobiomicslab

    Use when when you have a Windows-only .NET Framework 4.
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62. ▌
    Build System Configuration · holobiomicslab

    Use when when you have a Python package with source modules that need to be documented, want to generate API stubs automatically from docstrings, and need to produce browsable HTML documentation for distribution or hosting (e.g., on ReadTheDocs).
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63. ▌
    Class Hierarchy Extraction · holobiomicslab

    Use when you need to understand the extensibility surface of a modular object-oriented codebase, particularly when planning to contribute new modules, extend existing functionality, or onboard developers unfamiliar with the architecture.
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64. ▌
    Compound Metric Tabulation · holobiomicslab

    Use when after completing doAnalysis on a SummarizedExperiment object with mzQuality, when you need to share compound-level metrics with non-R users, integrate results into downstream reporting systems, or perform meta-analyses across multiple metabolomics experiments.
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65. ▌
    Conformer Generation Rdkit · holobiomicslab

    Use when when you have ionized adduct structures (SMILES or MOL format) from an ionization-state determination step and need to create an ensemble of relaxed 3D geometries for each molecule prior to expensive conformation filtering (e.g., ASE-ANI or quantum methods).
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66. ▌
    Count Matrix Preprocessing · holobiomicslab

    Use when after count matrix quantification (e.g., from Salmon) and before differential expression analysis, when you have: (1) a raw or unfiltered count matrix with potentially low-abundance features; (2) known batch effects or technical covariates documented in sample metadata;
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67. ▌
    Cross Domain Token Mapping · holobiomicslab

    Use when when building a unified sequence model (e.
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68. ▌
    Cross Platform Compilation · holobiomicslab

    Use when when releasing a new version of a tool, onboarding to a new development platform, or validating that a tool meets its documented platform support claims (e.g., Windows 10, Ubuntu 22.04, macOS 12+ ARM64). Apply this skill before publishing binaries or claiming multi-platform support.
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69. ▌
    Django Backend Development · holobiomicslab

    Use when you need to build a web-based data ingestion layer that accepts raw MS files (.raw, .mzML, .mzXML) from users, validates them before storage, and tracks their processing status through a data management pipeline.
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70. ▌
    Edge Case Boundary Testing · holobiomicslab

    Use when when implementing or validating a quantitative formula (e.g., resource sizing, memory allocation, worker count calculation) that will be applied across a range of input values, especially when the formula involves division, clamping, or has implicit domain constraints (e.
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71. ▌
    Feature Importance Ranking · holobiomicslab

    Use when after training logistic regression, random forest, and/or XGBoost classifiers on metabolomics data (e.
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72. ▌
    Formula Annotation Ranking · holobiomicslab

    Use when after generating candidate formula/adduct pairs from m/z database matching but before final metabolite annotation. Use it when you have observed isotopic patterns from feature detection (e.
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73. ▌
    Genomic Coordinate Mapping · holobiomicslab

    Use when after sub-clusters have been detected by PRESTO-STAT or PRESTO-TOP statistical methods on tokenised and redundancy-filtered BGCs, and you need to report their precise genomic positions, gene locus tags, and orientations for integration with natural product substructure predictions or for.
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74. ▌
    Graph Isomorphism Matching · holobiomicslab

    Use when when comparing two or more lipid structures and you need to determine which atoms and bonds in one structure correspond to those in another, prior to computing a distance metric. Specifically, when input lipids have variable fatty acyl chain compositions (e.
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75. ▌
    Graph Network Construction · holobiomicslab

    Use when you have trained ML models that predict pairwise relationships (e.
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76. ▌
    Interactive Plot Rendering · holobiomicslab

    Use when you have validated omics data loaded into R (expression matrices, fold-change and p-value pairs, gene ontology enrichment statistics, survival or distribution data) and need to generate publication-quality figures that must be explored interactively via a web browser, support pan/zoom, and.
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77. ▌
    Isobaric Ion Detection Msi · holobiomicslab

    Use when you have loaded MSI data with an extracted peak list and need to annotate matrix-related signals, particularly when the dataset may contain isobaric ions or peaks with overlapping spatial distributions that could be misclassified during downstream annotation filtering.
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78. ▌
    JSON Configuration Parsing · holobiomicslab

    Use when you need to implement a converter or standardization system that must map multiple incompatible nomenclature styles (e.g., lipid abbreviations from 5+ databases and 17+ software programs) into a single unified format.
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79. ▌
    Lipid Graph Representation · holobiomicslab

    Use when when you have multiple lipid structures (from lipidomics data in CSV, XLSX, or mzTab-M format) and need to compute pairwise structural distances, identify lipids responsible for shaping a lipidome, or perform hierarchical clustering of lipidomes.
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80. ▌
    Lipid Nomenclature Parsing · holobiomicslab

    Use when you have received raw lipid identification output from LipidSearch or LIQUID in CSV or TSV format containing lipid species names or identifiers, and you need to extract their structural components and map them to standardized LIPID MAPS categories before building a quantitative data matrix.
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81. ▌
    Long Format Data Reshaping · holobiomicslab

    Use when when you have a wide-format feature intensity table (samples in rows, analyzed compounds in columns) and need to conduct multiple regression linear models (lm or lmer) to estimate associations between independent variables (fixed effects) and each metabolomic feature as a dependent.
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82. ▌
    Longitudinal Data Analysis · holobiomicslab

    Use when you have imputed metabolomics data in long format (with id, time, categorical grouping variable, metabolite names, and numeric values) and need to rank metabolites by evidence of difference across groups or time trajectories.
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83. ▌
    Massbank Record Validation · holobiomicslab

    Use when you have a collection of MassBank records (in plain-text or structured format) that need to be systematically validated for conformance to MassBank format specification—particularly in a continuous integration context where validation must run on every commit or pull request to maintain.
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84. ▌
    Mean Intensity Aggregation · holobiomicslab

    Use when after importing imzML or vendor-specific MSI data into napari and visualizing the raw spectral dataset.
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85. ▌
    Metabolite Feature Ranking · holobiomicslab

    Use when you have an imputed, long-format metabolomics dataset with repeated measurements across subjects and a grouping variable (e.
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86. ▌
    Metabolite Pathway Mapping · holobiomicslab

    Use when after metabolite detection and normalization from Metabolomics Workbench format data, when you have a table of metabolite names or identifiers (rows=metabolites, columns=samples) and need to assign pathway membership to compute pathway-level enrichment statistics or visualize.
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87. ▌
    Metabolite Peak Annotation · holobiomicslab

    Use when after peak detection has identified significant m/z and retention time features in untargeted or targeted mass spectrometry data (as a .raw, .d, or mzXML file).
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88. ▌
    Metadata Structure Mapping · holobiomicslab

    Use when you have mzML-format raw data files from mass spectrometry experiments and need to ingest them into MS-DIAL for untargeted metabolomics or lipidomics analysis.
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89. ▌
    Metfrag Settings Injection · holobiomicslab

    Use when when deploying the ipbhalle/metfragweb container and you need to configure MetFrag parameters such as ChemSpider tokens, proxy settings for web services (MoNA, KEGG, MetaCyc), or local database connections (PubChem via MySQL/PostgreSQL) without modifying the container image itself.
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90. ▌
    Mzpeak File Format Parsing · holobiomicslab

    Use when when you have mass spectrometry data stored in mzPeak format (ZIP archive containing Parquet files) and need to read spectrum metadata, chromatogram metadata, and signal data (m/z and intensity arrays) for analysis. Use this skill if your input is an .
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91. ▌
    Per Pixel Array Arithmetic · holobiomicslab

    Use when you have multiple registered LA-ICP-MS elemental images (e.g., P31, Zn66 intensity maps) and need to compute a new derived image by applying per-pixel operations—such as elemental ratios, thresholding, masking, or conditional logic—across channels.
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92. ▌
    Pfam Domain Hit Extraction · holobiomicslab

    Use when you have BGC sequences (in FASTA or GenBank format) and need to identify conserved biosynthetic domains to build a feature vector for BGC similarity clustering or to annotate gene functions.
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93. ▌
    Port Mapping Configuration · holobiomicslab

    Use when when you have a containerized web application with a fixed internal port (e.g., Tomcat on port 8080) and need to expose it on a different localhost port for local access or testing.
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94. ▌
    Principal Curve Projection · holobiomicslab

    Use when you have per-sample metabolite abundance data and a metabolite-pathway association table, and you need to quantify dysregulation of individual samples across multiple metabolic pathways.
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95. ▌
    Projected Area Computation · holobiomicslab

    Use when you have 3D optimized molecular conformers (RDKit mol objects or SDF files) and need to extract shape-based features for collision cross section prediction, graph neural network input, or conformer comparison.
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96. ▌
    Pubchem Metadata Retrieval · holobiomicslab

    Use when after compound database dereplication (via SIRIUS or MetFrag) has produced per-spectrum candidate annotation lists with putative compound identifiers, and before applying selection criteria to rank and filter candidates.
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97. ▌
    Python Environment Pinning · holobiomicslab

    Use when when you have access to a research repository or README documenting a machine learning implementation (e.g., Keras/TensorFlow-based deep learning model) and need to reproduce the computational environment exactly. Triggers include: (1) README explicitly lists pinned versions (e.
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98. ▌
    Python Unit Test Execution · holobiomicslab

    Use when after rewriting or modifying a Python module (such as calculate_feature_overlap.py in a metabolomics analysis tool) and you need to verify that the refactored code maintains backward compatibility and correctness against the original test suite.
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99. ▌
    R List Object Manipulation · holobiomicslab

    Use when you have extracted metadata or spectral information from a Thermo Fisher Scientific .
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100. ▌
     R Package Function Mapping · holobiomicslab

     Use when you have a working R package (e.g., IonFlow for ionomics analysis) with documented functions and parameters, and you need to wrap it as a Galaxy tool so end users can invoke the R workflow through Galaxy's web interface without command-line expertise.
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