Integrations & APIs

holobiomicslab Skill

Use when after isotopologue and adduct grouping has been completed and you need to associate MS2 spectra with consolidated feature groups in DDA LC-MS experiments.

holobiomicslab Skill

Use when you have NMR peak data (1H and 13C chemical shift values) and need to obtain SMART 3 classification predictions from the DeepSAT service.

holobiomicslab Skill

Use when you need to verify that a Python package (or similar installable software) passes its declared integration test suite as a prerequisite to trusting its reliability in production or downstream analysis. Specifically, apply it when you observe a periodic testing CI workflow badge (e.

holobiomicslab Skill

Use when you have a Python webservice codebase (e.g., a Flask, Django, or FastAPI application) and need to document its HTTP API surface (endpoints, methods, parameters, schemas, authentication) for integration, testing, or specification generation.

holobiomicslab Skill

Use when when building asynchronous metadata enrichment workflows that call multiple external APIs (CIR, CTS, PubChem, IDSM, BridgeDb) to annotate mass spectra .

holobiomicslab Skill

Use when you have a mature C++ library (like OpenMS) with stable APIs that you want to make accessible from Python environments, and you need to preserve performance-critical C++ execution while supporting rapid prototyping or integration into Python-based data pipelines (e.

holobiomicslab Skill

Use when when a Shiny application currently uses orca for static plot export but requires a lighter-weight, Python-native alternative that avoids Node.js/Electron runtime overhead.

holobiomicslab Skill

Use when you have raw or processed TWIM-MS data with arrival time and m/z dimensions, and you need to assign biomolecular class labels and compute class-specific CCS values across multiple compound classes simultaneously, particularly when you lack pre-identified feature peaks or want to bypass.

holobiomicslab Skill

Use when when you have matched multiomics measurements across the same samples or cell lines (transcriptomics, proteomics, metabolomics, epigenomics, etc.) and need to train predictive models that learn regulatory relationships across biomolecular classes.

holobiomicslab Skill

Use when you have a batch of chemical compounds (identifiers and structures in SMILES, InChI, or IUPAC format) that need to be submitted to a remote REST API for classification or analysis, and you require the server's response (query ID and status) to track or retrieve results asynchronously.

holobiomicslab Skill

Use when after peak clustering has been performed on aligned GCIMS samples and a peak table matrix has been constructed, but the matrix contains NA values because some samples did not yield detected peaks at certain cluster positions.

holobiomicslab Skill

Use when you have a batch of mass spectra records in .msp format that lack standardized metadata fields (SMILES, InChI, CAS numbers, molecular formula, IUPAC names) and need to populate them by querying multiple independent web APIs in parallel.

holobiomicslab Skill

Use when after organism names have been cleaned and standardized (e.g., via 1_cleaningOriginal.R and 4_cleaningTaxonomy.R) but before final integration of organism, structure, and reference data. Use it when you have a cleaned organism table (interim/tables/2_cleaned/organism/cleaned.tsv.

holobiomicslab Skill

Use when after organism name cleaning and standardization (via 1_cleaningOriginal.R and 4_cleaningTaxonomy.R) has produced a cleaned organism table (interim/tables/2_cleaned/organism/cleaned.tsv.gz), apply this skill to map those cleaned names to Open Tree of Life (OTL) identifiers.

holobiomicslab Skill

Use when when you receive a raw query string destined for the ClassyFire API and need to distinguish between a user-supplied compound identifier (e.g., a database accession or common name) and the actual chemical structure representation (SMILES, InChI, IAPNIC name, or FASTA sequence).

holobiomicslab Skill

Use when you need to expose all supported metadata conversion options in a tool interface (e.g., Galaxy tool form, CLI argument parser, or API endpoint) and want to avoid hard-coding conversion paths.

holobiomicslab Skill

Use when when you have downloaded pre-trained Keras models and need to confirm their layer naming and structure conform to requirements for TensorFlow Serving or other deployment pipelines—specifically before converting to HDF5 format or integrating into a production API that expects fixed.

holobiomicslab Skill

Use when when you have converted multidimensional MS data to MZA HDF5 format and need to programmatically read spectra, metadata, and ion mobility or mass-to-charge arrays in Python or R without vendor-specific dependencies.

holobiomicslab Skill

Use when you need to submit structured chemical compound data (identifiers and structural representations) to a remote REST API that accepts POST requests and returns JSON responses, particularly when the API requires tab-separated compound inputs separated by newlines and a query label as the.

holobiomicslab Skill

Use when you have pre-trained neural network models (e.g., Keras/TensorFlow) for chemical classification and need to expose them as a queryable HTTP service.

holobiomicslab Skill

Use when you have LC-MS peak tables from parallel unlabeled and labeled (isotope-traced) sample cohorts, sample metadata defining groups and conditions, and you seek to identify metabolic intermediates that accumulate differentially in a perturbed system (e.

holobiomicslab Skill

Use when when extending an existing neural network class (e.g., SiameseModel) that lacks user-configurable regularization, and you need to prevent overfitting on moderate-sized training datasets (e.

holobiomicslab Skill

Use when after completing Part 4 (Identification of ISF Features) in the ISFrag workflow, when you have a feature table with identified ISF features and their hierarchical fragmentation relationships, and you need to export this relationship structure for interpretation, integration with external.

holobiomicslab Skill

Use when when you need to construct a POST endpoint that ingests raw spectral data files from multiple vendor formats (jcamp, RAW, mzML) and must standardize them for downstream processing.

holobiomicslab Skill

Use when you have intensity measurements (peak features, protein intensities, or gene expression values) with compound or gene annotations (KEGG IDs, ChEBI IDs, UniProt IDs, or ENSEMBL IDs), and you need to aggregate them into biologically meaningful pathway groups for differential analysis.

holobiomicslab Skill

Use when when you have implemented or modified a data ingestion module (e.g., mzML parser) and need to verify that file deserialization produces correct internal representations.

holobiomicslab Skill

Use when you need to create a new backend to integrate MS data from a novel file format, database, or in-memory storage system into the Spectra ecosystem. Use this skill when existing backends (MsBackendMemory, MsBackendMzR, MsBackendSql, etc.) do not support your data source or storage paradigm.

holobiomicslab Skill

Use when you have standalone metabolomics analysis tools (Python scripts, R packages, MATLAB compiled applications) that you want to expose through Galaxy's UI and make composable into reproducible workflows.

holobiomicslab Skill

Use when you have chemical annotations (GNPS spectral library matches) assigned to MS/MS samples and a validated ReDU sample-information template (TSV) with categorical metadata (e.g., sample type, extraction method, ionization source).

holobiomicslab Skill

Use when you have generated a GNPS molecular network (classical or feature-based workflow) and possess chemical class annotations (from GNPS library matching, ClassyFire, or other structural classifiers) that you wish to propagate onto network nodes and edges to enable chemical family-level.

holobiomicslab Skill

Use when after completing feature detection, alignment, and optional filtering (blank subtraction, QC reproducibility, feature occurrence thresholds) in MZmine2 or Optimus, and you need to prepare the feature table and MS/MS spectra for GNPS-based molecular networking, bioassay integration, or.

holobiomicslab Skill

Use when after completing feature annotation with the annotateRC function on LC–MS All-ion fragmentation (AIF) datasets, when you need to persist ranked metabolite candidates, matched ion spectra, and global summary tables to disk for archival, manual review, or integration into downstream.

holobiomicslab Skill

Use when you have an LC-HRMS feature table (m/z, retention time, isotope ratios, fragmentation patterns) and a suspect compound database with reference properties (m/z, expected RT windows, theoretical isotope ratios, characteristic neutral losses), and you need to rank which features most likely.

holobiomicslab Skill

Use when you have (1) a GNPS molecular network (classical or feature-based) with cluster/feature identifiers, (2) MS2LDA output containing Mass2Motif assignments with probability and overlap scores for those same clusters/features, and (3) a goal to annotate network nodes with substructural and.

holobiomicslab Skill

Use when when you need to validate that a package's periodic integration test suite (distinct from unit tests) passes as expected, or when you must collect and communicate structured evidence of test outcomes across multiple test cases.

holobiomicslab Skill

Use when when you have conducted batch MS/MS searches across one or more domain-specific MASST tools and need to combine their hit scores, metadata annotations, and taxonomic lineages into a single coherent result set for comparative analysis or publication.