Claude Skills by HolobiomicsLab

Use when you have CE-MS test files archived in the msdata Bioconductor package and need to load them into an in-memory or on-disk R representation to extract ion electropherograms, pick peaks, or compute effective mobility transformations.

Use when you have raw or processed TWIM-MS data with arrival time and m/z values for multiple features, but lack prior structural identification (e.g., from spectral libraries or databases).

Use when after peak recognition has identified significant m/z signals in individual breath samples and you need to aggregate features by sample identifier before aligning features across multiple samples.

Use when when you have a large reference MS/MS spectral library (>10k spectra) and need to perform open modification searches on query spectra without exhaustively comparing against every library entry.

Use when you have raw CE-MS instrument output in mzML or netCDF format and need to extract specific ion traces (by m/z value), filter by effective mobility windows, or apply transformations to migration time data.

Use when when processing CE-MS test files and you need to identify and extract the migration time of the EOF marker (e.g., Paracetamol) to normalize compound migration times across runs.

Use when when processing raw CE-MS data and need to establish a baseline migration time scale before transforming to effective mobility.

Use when your CE-MS dataset exhibits migration time drift between runs due to electroosmotic flow (EOF) variation, and you have identified two internal mobility markers (e.g., Paracetamol and Procaine) with known charges whose migration times can be measured in the raw data.

Use when when you have received chemical annotations from GNPS spectral library matching workflow and need to assess their reliability before downstream analysis (e.g., chemical explorer visualization, sample filtering, or comparative metabolomics).

Use when you have selected a subset of public tandem MS files from ReDU/MassIVE that have been processed through GNPS spectral library matching, and you need to organize their chemical annotations into a matrix (rows = files, columns = annotated features) before performing PCA or other multivariate.

Use when when you have pre-computed embeddings for query and reference MS/MS spectra, computed their cosine similarity matrix, and need to measure retrieval success by verifying whether the correct compound (identified by SMILES string) appears in the top-1, top-5, or top-10 ranked candidates from.

Use when you need to understand how a data-processing software system discriminates among multiple input types (LC, GC, IMS, MALDI) and selectively instantiates processing pipelines.

Use when you have detected a single chromatographic peak in DDA LC-MS/MS data that generated multiple MS2 fragmentation spectra (e.

Use when when comparing two MS/MS spectra (query and reference) to quantify their spectral resemblance for compound identification or molecular networking, particularly when you need a simple, symmetric measure that is insensitive to precursor mass differences and does not require peak alignment.

Use when after generating normalized dense embeddings for both query and reference MS/MS spectra using a pre-trained model like SpecEmbedding.

Use when when you have pre-computed spectral embeddings (vectors) for both query spectra and a reference library, and you need to measure retrieval performance by ranking reference compounds by similarity to each query.

Use when you have preprocessed and normalized ROI feature data extracted from mzXML or mzML mass spectrometry files and seek to increase feature representation and robustness before statistical modeling or machine learning.

Use when you have a derivatizing matrix (e.g., TAHS or other publicly documented reagent) with known composition and ionization behavior that you want to use in Met-ID for metabolite annotation, and the matrix is not yet configured in your Met-ID installation.

Use when when you have CE-MS data with migration times that vary between runs due to electroosmotic flow drift, but you possess a reliable internal standard with a known effective mobility value.

Use when you have raw CE-MS data (mzML or netCDF format) with migration time measurements and need to establish a reproducible compound-specific axis that is independent of run-to-run electroosmotic flow fluctuations.

Use when you have a query electron ionization (EI) mass spectrum in msp format and wish to identify it by matching against a reference spectral library. Apply this skill when you need ranked similarity scores between the query and each library entry to prioritize candidate identifications.

Use when you are preparing to perform effective mobility transformation of CE-MS data and must establish the electrophoretic system's calibration context.

Use when you have CE-MS raw data (mzML or netCDF format) containing a target compound of known m/z ratio and you need to resolve it as a distinct peak on the effective mobility scale rather than migration time scale.

Use when when implementing or validating a lossy numeric codec for mass-spectrometry data (e.g., MSNumpressCoder in OpenMS). Specifically: after implementing both encoder and decoder, before shipping to production, or when comparing alternative compression schemes.

Use when you have a tandem MS/MS spectrum of a structurally modified compound and a known reference structure (SMILES), and you need to annotate which fragment ions correspond to specific bonds or atoms in the molecule.

Use when after feature detection and alignment have produced a feature table with MS/MS spectra, and you have access to a reference spectral database (e.g., xenobiotic reaction libraries or public databases).

Use when when comparing GNPS chemical annotations across two or more groups of samples (defined by ReDU sample-information categories such as sample type, extraction method, or ionization source) where the groups contain different numbers of files.

Use when when you have raw or preprocessed mass spectrometry imaging (MSI) data with limited spatial resolution, high noise, or incomplete molecular coverage, and you want to enhance signal fidelity to support multiscale tissue–single-cell mapping or brain biochemical profiling.

Use when when you have computed PCA coordinates from chemical annotation matrices (e.

Use when you have CE-MS raw data (mzML or netCDF format) containing a known target analyte with a precise m/z value, and you need to isolate its signal within a defined effective mobility window (e.

Use when you have raw LC-HRMS metabolomics data in .mzML or .

Use when you have raw MS data files in vendor-native format (.raw, .d, .ms) from CE-MS or LC-MS instruments and need to process them through AriumMS or other open-source metabolomics pipelines that require standardized XML-based interchange formats.

Use when you have uploaded MS/MS data to MassIVE with validated sample-information metadata and need to subset public files by sample attributes (organism, tissue type, extraction method, ionization source, pre-MS separation) to create reproducible, manageable cohorts for molecular networking.

Use when when building a re-usable spectral reference library for lipidomics workflows where you need to match experimental MS/MS spectra against a comprehensive theoretical fragmentation model.

Use when when you have an unknown MSMS spectrum (precursor m/z and fragment ions) and need to discover structurally related compounds from a spectral library.

Use when you have an experimental MS/MS spectrum (e.g., from MassBank or acquired data) for a single metabolite with known accurate precursor m/z and adduct type, and you need to generate a library entry with scored fragments for use in metabolite annotation pipelines.

Use when when comparing two or more MSMS spectra using intensity-weighted similarity measures (cosine similarity, modified cosine, or neutral loss similarity), and the spectra have been acquired under different instrumental conditions, ionization efficiencies, or detector gains that produce.

Use when extracting migration times of specific analyte or reference markers (e.g., Paracetamol EOF marker) from CE-MS files using peak-picking workflows.

Use when you have mass spectrometry data in mzXML or mzML format and need to systematically extract regions of interest (ROIs) from multi-dimensional m/z-intensity-time arrays, normalize feature values, and augment datasets for untargeted metabolomics workflows.

Use when when you have an untargeted metabolomics feature table (m/z values, retention times, intensities) and aim to predict functional pathway activity without explicit metabolite identification.

Use when after GNPS spectral library matching has been completed on a batch of MS2 spectra from public MassIVE datasets and you need to aggregate chemical annotations into a tabular format suitable for downstream comparative metabolomics, co-analysis, or chemical explorer visualizations across.

Use when you have selected a subset of ReDU public tandem MS files with GNPS chemical annotations (level 2 or 3 spectral library matches) and wish to explore sample relationships via principal component analysis.

Use when you have an experimental MS/MS spectrum (from MassBank or your own acquisition) and need to create a standardized library entry with ranked fragment ions for use in MetaboAnnotatoR or other fragment-based annotation pipelines.

Use when when preparing to process raw LC-HRMS metabolomics data (.mzML or .abf files) with MS-DIAL within a Nextflow pipeline, before executing peak detection and chromatogram alignment.

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).

Use when you have OnDiskMSnExp CE-MS objects with known marker compounds (e.g., Paracetamol EOF marker) and need to extract their migration time positions to establish a calibration reference.

Use when after computing compareSpectra similarity scores between an experimental consensus MS2 spectrum and candidate reference spectra (e.

Use when analyzing CE-MS(/MS) data where electroosmotic flow fluctuations cause variable migration times for the same compounds across runs.

Use when you have MS/MS spectra in .msp format and need to retrieve similar compounds or compute spectral similarities for compound identification. The input spectra should already be cleaned (malformed or invalid SMILES removed), and you have access to a pre-trained SpecEmbedding model checkpoint.

Use when you have two or more molecular structures (represented as SMILES or spectral data) and need to rank transformation product candidates by structural plausibility, filter isomeric or duplicate TP predictions, or group features into components based on chemical relatedness.