Use when you need to verify claims about algorithm performance, data processing correctness, or workflow outcomes in a scientific article or software repository.
Use when you have a GNPS mass spectral molecular network (in graphml or cytoscape format) and want to enrich its nodes with chemical class information derived from GNPS public…
Use when after running qc_summary() on a filtered mpactr object when you need to understand the distribution of ions across filter status categories (passed vs.
Use when when you have mass spectrometry data stored in non-standard formats (SQLite, HDF5, custom binary) that pymzML does not natively support, and you want to enable…
Use when you are setting up a new LipoCLEAN analysis for MS-DIAL output and need to create a configuration file tailored to your MS-DIAL version (4 or 5).
Use when you have raw lipidomic and metabolomic data files generated by the Multi-ABLE method (high-pressure liquid chromatography–mass spectrometry output) and need to p — from…
Use when when processing mass spectrometry imaging (MSI) data in positive ion mode where both [M+H]+ and [M+Na]+ adducts are present for the same lipid species, and you observe…
Use when you need to obtain source code or computational workflows from a published repository, particularly when the article explicitly provides a GitHub URL and documents that…
Use when you have extracted retention times at peak maxima (rtFittedAPEX) from extracted-ion chromatograms (XICs) of known internal RT calibrants (e.
Use when immediately after parsing and validating raw LC-MS/MS data files (mzML, mzXML, or vendor formats) when you need to prepare spectral data for fragmentation tree…
Use when you have GCIMS samples exhibiting misalignment across drift time (typically 5–16 ms range) and retention time (typically 0–1100 s range) caused by pressure/temperature…
Use when when you have extracted file metadata or scan summaries as R list objects from .raw files using readFileHeader(), readIndex(), or readSpectrum(), and need to persist them…
Use when when you have raw or preprocessed 1H NMR spectral tensors from flavor or chemical mixtures and need to generate high-level feature representations that capture both…
Use when after differential peak analysis (tl.diff_test) has identified peaks that differ in accessibility across cell types or conditions.
Use when you have imported a raw LA-ICP-MS raster image (line-by-line, spot-wise, or ablation-time-aligned format) and need to isolate tissue regions from instrumental background…
Use when you have aligned feature tables (CSV format) paired with MS2 spectral data (MGF or mzML files) and need to compare chemodiverse samples with poor feature overlap or…
Use when after mass tracks have been aligned across samples into a MassGrid structure and retention time calibration dictionaries (rt_cal_dict) have been computed for eac — from…
Use when building a multi-source metadata annotation pipeline where converters are organized as dynamically discoverable subclasses in separate packages (e.g.,…
Use when when performing targeted quantification of known compounds in LC-MS data using TARDIS, especially when the instrument acquired data with multiple overlapping m/z scan…
Use when you have a dashboard_data.json file (JSON export from the msFeaST pipeline) and need to interactively explore quantification tables, metadata, and spectral data on a…
Use when you have SWATH-MS raw data (mzML or vendor format) from an untargeted metabolomics experiment and need to identify metabolites.
Use when you have instantiated a learned component (embedding layer, encoder, or transformer submodule) from a published codebase and need to verify that its forward pass produces…
Use when when processing large collections of mass spectra from multiple Open Mass Spectra Libraries (OMSLs) or databases that may contain redundant spectral records with…
Use when you have raw mass spectrometry data (vendor formats, mzML, or existing mzPeak files) and need to: (1) convert to mzPeak format for long-term storage and interoperability…
Use when you have a GNPS-generated molecular network (graphml or JSON format) and corresponding MS2LDA experiment results or chemical class assignments, and you want to annotate…
Use when after running MetaboAnnotatoR's annotateRC function when you need to (1) verify that the top-ranked annotation for a feature is correct, (2) understand what alternative…
Use when you have executed batch searches of MS/MS spectra against multiple domain-specific MASST tools and need to synthesize results across domains (e.
Use when you have loaded raw Agilent Unknowns Analysis CSV output with required columns (Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when when ingesting raw LC-MS/MS output from a mass spectrometry instrument and you need to prepare it for metabolite identification, fragmentation tree computation, or…
Use when you have a set of metabolite structures (or their molecular descriptors) and need to construct training or target feature matrices for CCS prediction.
Use when after you have processed raw LC-MS/MS spectral data through the specXplore importing pipeline in a Jupyter notebook and produced an in-memory specXplore session data…
Use when after generating normalized dense embeddings for both query and reference MS/MS spectra using a pre-trained model like SpecEmbedding.
Use when you have LC-IM-MS/MS experimental data (raw mzML or vendor format) containing signals from N-Me derived unsaturated sterol lipids and need to assign double-bond positions…
Use when you have spatial metabolomics data with semicolon-delimited isomer name annotations (such as the 'all_IsomerNames' column in SpaMTP Seurat objects) and you need to reduce…
Use when you have raw or preprocessed MS imaging data archived as an RDS file or from a Zenodo deposit that includes the full m/z feature set (e.g., 10,200 m/z values spanning…
Use when when implementing or extending file format parsers in a spectral data pipeline, you need unit tests to ensure that format-specific parsers correctly instantiate spectrum…
Use when when you have computed pairwise distances between MS2 fingerprint vectors from multiple metabolomics samples and need to visualize sample similarity relationships in low…
Use when you have raw MS data in vendor formats (Agilent .d, Thermo .raw, Bruker .
Use when you have nuclear magnetic resonance (NMR) peak data (proton 1H and carbon-13 13C measurements) that you need to classify using a deployed deep learning model, and you…
Use when when you have raw MS/MS spectra in MGF or mzML/mzXML formats and need to feed them into Casanovo or similar transformer-based de novo sequencing models.
Use when after baseline correction (e.g., via asymmetric least squares) when raw GCxGC-MS chromatograms still contain high-frequency noise that obscures true signal structure.
Use when after computing a pairwise sample distance matrix from aligned MS2 fingerprint vectors and you need to visualize sample relationships, clustering, or separation by group…
Use when you have structural input data (SMILES or molecular geometry files) for N-Me derived unsaturated sterol lipids and need to generate a predicted CCS dataset indexed by…
Use when when you have mzPeak format spectrum files and need to work with spectrum metadata, intensity/m/z arrays, or precursor information in a tabular, columnar, or vectorized…
Use when when comparing two MS/MS spectra using modified cosine similarity and the precursor m/z values differ, indicating potential neutral losses, adduct variations, or analogs…
Use when you have a generic genome-scale metabolic model (SBML format) and cross-sectional omics data (RNA-seq, intracellular metabolomics, extracellular flux measurements from…
Use when when you have imported raw mass spectrometry spectral data (in formats like mzML, mzXML, msp, MGF, or JSON) and need to clean peak lists before metadata validation,…
Use when when you have raw or processed TWIM-MS data (arrival time and m/z values) from a mass spectrometry instrument and need to organize it into a feature table before…
Use when before launching the DaDIA metabolomics pipeline or any multi-package workflow, when you have an R environment with potentially mixed or unknown package versions and need…
Use when you have LC-MS/MS DDA data from one or more samples and need to organize fragmentation spectra by similarity relationships to support compound annotation, enable…
Use when evaluating alternative implementations of data storage or retrieval strategies in R objects—specifically when deciding whether to eagerly populate all columns in a data…
Use when you have LC- or GC-HRMS data in mzML format and a feature list (CSV/TSL/Excel) from external feature detection software (e.
Use when when you have a USI string (e.g., mzspec:GNPS:TASK-d93bdbb5cdda40e48975e6e18a45c3ce-f.mwang87/data/Yao_Streptomyces/roseosporus/0518_s_BuOH.
Use when after loading and formatting raw peak-picked LC-MS metabolomics data frames (via metabData constructor) when you need to eliminate features with poor sample coverage…
Use when processing spectral datasets from open mass spectra libraries (OMSLs) where structural identifiers and ionization metadata are incomplete or inconsistent.
Use when you have a shallow decision tree trained on ChemEcho feature vectors (peak or neutral loss formulas) and need to deploy it as an executable query against tandem mass…
Use when after identifying differentially methylated bases or regions (via calculateDiffMeth() and getMethylDiff()), when you need to characterize WHERE these methylation changes…
Use when you have paired microbiome and metabolomic (or similar compositional) data with a new regression model and want to rigorously demonstrate its predictive advantage over…
Use when you have ion-mobility mass spectrometry metabolomics data with putative metabolite identifications (e.g., from database matching) and want to reduce false positives by…
Use when you have untargeted metabolomics data with unknown or ambiguous molecular identities, anchor metabolites (known structures in SMILES or MOL format), and a curated…