Use when when constructing a composite loss function for contrastive learning on structured data (e.
Use when when exporting quantified MSI data (feature-by-pixel intensity matrices with associated ion m/z, lipid annotations, and pixel spatial coordinates) from LipidQMap and you…
Use when when you have a list of known metabolite concentrations and their corresponding J-coupling constants (spin systems) and need to generate realistic 1D 1H NMR spectra or 2D…
Use when after bias-correcting ATAC-seq cutsite signal (via ATACorrect) when you have a bias-corrected bigWig file and need to compute per-position footprint scores within defined…
Use when when comparing experimental spectra to reference library spectra and fragment ion m/z values show systematic drift or measurement noise that could distort neutral loss…
Use when after componentization of parent and TP features with generateComponents(algorithm='tp'),
Use when you have normalized peak intensities using MetaboDirect's data preprocessing step and are preparing to perform PERMANOVA or NMDS ordination on a bacterium-phage or…
Use when when you have .mzML or .abf LC-HRMS raw data files that require MS-DIAL-based feature detection, chromatogram alignment, and metabolite identification, and you need to…
Use when you have predicted structural similarity scores (e.g., Tanimoto or Dice scores) for a large set of spectrum pairs and need to assess prediction accuracy across the full…
Use when you have corrected ATAC-seq footprint scores (from ATACorrect and ScoreBigwig) at open chromatin regions and a motif database (e.g., JASPAR PWMs), and you need to…
Use when when working with raw GC-MS data in NetCDF (ANDI) format that requires peak detection, baseline removal, and retention time alignment before spectral matching against…
Use when you have defined one or more proton NMR spectral regions-of-interest (ROIs) with lower and upper chemical-shift bounds (in ppm) from an experimental NMR spectrum of a…
Use when after marker identification or feature selection has produced a list of discriminatory m/z features, and before pathway enrichment analysis (e.g., KEGG).
Use when you have sequential QCpool (pooled quality control) samples analyzed with Sciex Multiquant (≥v3.0.
Use when when designing injection sequences for LC/GC-MS multi-omics experiments where you need to distribute samples across multiple plates and must account for mandatory QC…
Use when you have a collection of N scripts (e.g., 19 gallery examples) that must run on multiple backends or configurations, and you need to produce a reproducible benchmark…
Use when you have mass spectrometry data arriving through heterogeneous input formats (Task ID from GNPS, Universal Spectrum Identifiers, or Feature-Based Molecular Networking…
Use when building or extending a data extraction and conversion system (such as MESSES) where tabular data is transformed via conversion directives into JSON intermediate formats…
Use when you have raw CE-MS data and need to (1) transform migration time values to effective mobility using two calibration markers (e.
Use when you have raw MS/MS spectral data in one or more standard mass spectrometry file formats (.mgf, .msp, or .mzML) and need to convert them into a standardized…
Use when after organism name cleaning and taxonomy verification (4_cleaningTaxonomy.R) have been completed and you have a cleaned organism table with standardized names.
Use when when you have loaded a project JSON document from the Pairing Omics Data Platform and need to identify and document constraint violations (such as whitespace in URL…
Use when a scientific Python package is being moved to a new GitHub organization with different structural conventions (e.g., from a personal lab account to a community-led…
Use when you have raw ChIP-Seq and control BED files with potential PCR duplicates or unequal sequencing depths.
Use when you have a raw NV (NMRViewJ) binary file and need to confirm it is well-formed before parsing or processing.
Use when you have preprocessed 1H NMR spectral data with compound labels and need to identify multiple compounds in a flavor mixture where both local spectral patterns (handled by…
Use when you have raw peak area or intensity measurements for both compounds and their corresponding internal standards across all study samples (including QC and calibration…
Use when you have two independent LC-MS untargeted metabolomic feature tables (e.
Use when during MSP, MGF, JSON, or CSV file parsing when standardizing mass spectra from heterogeneous open mass spectral libraries (OMSLs).
Use when you have imaging mass spectrometry (IMS) datasets where peak intensities are high-dimensional and sparse, and you need to extract compressed latent features that preserve…
Use when you have a parent compound (or set of compounds) in SMILES, MOL, or SDF format and need to predict plausible metabolite structures and pathways in a specific biological…
Use when when using mpactr filter functions (e.g., filter_mispicked_ions, filter_group, filter_cv) with R6 reference semantics and uncertain whether the copy_object parameter…
Use when you need to generate blank or background-only .mzML files for method validation, when you want to create synthetic negative controls with realistic instrumental noise but…
Use when you need to create realistic, diverse chemical populations for simulating LC-MS/MS acquisition strategies in a virtual environment.
Use when you have a set of query chemicals (chemical names or structures) and need to match them against a reference chemical library organized by type or category, with the goal…
Use when you observe jagged or noisy peak profiles in low-abundance ions after loading raw IM-MS data (Agilent MassHunter .
Use when you have an experimental mass spectrum (or a set of spectra from LC-MS/MS data) and need to identify the underlying metabolite(s) by comparing against known reference…
Use when converting raw MS/MS spectra from library files (e.g., .msp format) into structured library entries, or when annotating experimental LC–MS features against fragment…
Use when you have LC-HRMS raw data files (.mzML or .abf format) from metabolomics experiments and need to extract, align, and annotate features in a reproducible manner across…
Use when after identifying differentially methylated bases or regions (via calculateDiffMeth() and getMethylDiff()), when you need to characterize WHERE these methylation changes…
Use when after sample alignment and grouping of isotopologues and adducts have been completed, when the aligned feature table contains NA or zero entries (missing intensities) for…
Use when you have experimental fragment m/z values from HRMS/MS instruments (Q-Exactive orbitrap, Q-TOF) in CSV or mzML-derived peaklist format, and need to match them against a…
Use when after computing per-bin coverage depth using cooltools.coverage() on a loaded cooler object, when you need to (1) share the coverage track with non-Python tools, (2)…
Use when you have 1H NMR spectral tensors as input and need to extract local features (e.g., peak patterns, signal neighborhoods) before applying attention-based or sequence-level…
Use when you have peak-picked LC-MS data with multiple features that may represent the same metabolite detected at slightly different m/z or retention time values due to…
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.
Use when after you have identified a set of differentially methylated bases or regions (e.
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…
Use when you have raw mzML files and corresponding feature tables (CSV format, mzmine-formatted) from untargeted LCMS experiments, and you need to convert them into…
Use when when annotating .msp files with metadata from multiple external web services and you need to monitor which services are slow or unreliable.
Use when you have a pre-trained TCN spectrum encoder, annotated MS/MS spectra paired with ground-truth molecular formulas, and you want to train only the formula ranking and…
Use when when you have access to source code or algorithmic documentation of a metabolite generation pipeline (such as MAGMa's job subproject) and need to understand, validate, or…
Use when when training a regularized deep neural network for molecular property regression (e.g., retention time prediction on the METLIN SMRT dataset with 80,038+ samples), use…
Use when when you have preprocessed MS/MS spectra converted to a bag-of-fragments
Use when you have GC-MS data with multiple replicate injections or samples, need to identify a predefined set of query chemicals by name, and want to consolidate all instances of…
Use when you have a .msp format MS/MS spectrum library (e.g., from MassBank or similar public databases) and need to convert it into individual CSV entries indexed by positive or…
Use when you have mass spectrometry MS/MS spectral data in GNPS-style MGF format and need to feed it into the Mass2SMILES deep learning model for structure and functional group…
Use when you have GNPS library accession IDs (e.g. CCMSLIB00011906190) for a reference compound and a chemically or biologically modified analog, and need to load their full MS/MS…
Use when initializing a Dataset object in NMRFx and must decide which storage backend to use for in-memory or memory-mapped file access.
Use when you have MS-DIAL lipid identification results (alignment exports in msp/txt format) and need to distinguish correct from incorrect lipid IDs before downstream analysis.