Use when when you have raw mass spectrometry transition data from a triple-quadrupole
Use when after structural clustering (isotopologue grouping, adduct detection, cross-assay linking) and correlation clustering of LC-MS features, when you need to inspect and…
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 run a spectral networking job on GNPS (e.g. ProteoSAFe-METABOLOMICS-SNETS-V2) and need to reuse the network output files locally with MetaMiner or another…
Use when you have mzML or mzXML mass spectrometry data files and need to extract and validate spectral records (m/z and intensity arrays) for lossless compression, lossy…
Use when when you have modifications to propose for a shared codebase (e.g., bug fixes, new features, or documentation updates) and need to integrate them without disrupting the…
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 when annotating full-scan MS or MS imaging data against a metabolite database (e.g., LipidMaps, HMDB) and you need to control the stringency of m/z matching.
Use when after running Enrichment() on a configured EnrichParam object (via KEGG_Enrich_PlotPanel or similar), when you have a full enrichment result table and need to reduce it…
Use when you have trained a shallow decision tree on ChemEcho feature vectors (representing unique peak or neutral loss formulas from tandem MS spectra) and need to deploy the…
Use when after training a NeatMS CNN model on labeled MS1 peaks and generating predictions on a held-out test set, compute ROC-AUC to assess whether the model achieves the target…
Use when when you have a pre-trained GNN checkpoint and a smaller, task-specific
Use when when evaluating whether a mass spectrometry analysis platform (such as mzmine) has comprehensive module support across multiple ionisation and separation techniques (LC,…
Use when when you have imported a tab-delimited metabolomics file (via readData or similar) containing columns for compound identifiers, sample/aliquot names, peak areas (primary…
Use when you have a metabolite intensity matrix (rows=metabolites or peaks, columns=samples) paired with metabolite-to-pathway or metabolite-to-feature-group annotations, and you…
Use when you have a connected subnetwork of LC-MS features that matched isotope or adduct patterns, and you need to establish a canonical tree representation with a single neutral…
Use when you have prototyped a novel data-dependent acquisition strategy that uses dynamic exclusion with intensity or ROI weighting, and you need to quantitatively compare its…
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 a Python module declares optional/conditional dependencies (e.g., sqlalchemy for database access) and you need to confirm that the module can be imported and instantiated…
Use when when you have raw methylation array data (450K or EPIC format) in .idat files or as a beta-valued matrix and need to conduct a complete analysis pipeline including data…
Use when after bias-corrected ATAC-seq signal tracks (bigWig files) have been generated and you need to quantify transcription factor binding strength within open chromatin…
Use when training a contrastive learning model on ion image data (mass spectrometry imaging) where augmented pairs of the same ion image must maximize similarity while different…
Use when you have IM-MS lipidomics data from samples spiked with U13C-labeled internal standards (fully labeled yeast extract) and you need to quantify whether measured C — from…
Use when when preparing to create a release branch in a Maven-based multi-module
Use when you need to generate a comprehensive, non-redundant inventory of lipid species that span a defined lipid class (e.g., phosphatidylcholine, triacylglycerol) and a range of…
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…
Use when you have retrieved and deduplicated chemical formulae and metadata from multiple heterogeneous sources (HMDB, ChEMBL, PubChem) and extracted both structural relationships…
Use when you have a baseline GNN model trained on a molecular property prediction task (e.
Use when you have raw MS/MS spectra in MGF or other standard formats that need to be ingested into a machine learning pipeline for cross-modal matching against molecular…
Use when after m/z grouping and pairwise alignment detection when you have a metabCombiner object containing candidate feature pair alignments and need to select a subset of…
Use when when you have a small set of matched reference features (isolated, high-quality chromatographic peaks from reference chromatograms that have been aligned to a…
Use when building a multi-source metadata annotation pipeline where converters are organized as dynamically discoverable subclasses in separate packages (e.g.,…
Use when you have raw or unprocessed MS/MS spectral data in standard metabolomics formats (MGF, mzML, mzXML, msp, or JSON) and need to import them into a Python-based workflow for…
Use when you have a query mass spectrum (or representative metabolite spectrum from public data) and need to identify it by searching against large spectral reference databases…
Use when when you have an unknown mass spectrum (query spectrum) and need to search it against a reference database of billions of spectra to find matching or structurally related…
Use when when comparing mapping performance between two mapper implementations (e.g., C++ salmon vs. Rust salmon), validating that a bug fix or algorithmic change did not degrade…
Use when releasing a new version of a Python package to public repositories, when verifying that distribution pipelines are functioning after code changes, or when troubleshooting…
Use when when you have peak-abundance .csv files with assigned molecular formulas (elemental composition: C, H, O, N, P, S) from FT-ICR MS or high-resolution MS and need to…
Use when when you have a neural network or machine learning model with multiple tunable hyperparameters (layer size, regularization strength, dropout) or design choices (e.
Use when you have raw MS/MS feature data with m/z, retention time, and fragmentation spectra from an untargeted metabolomics experiment, and you need to annotate reaction-derived…
Use when you have transcript-level quantification output files (quant.sf, quant.gz) from salmon, kallisto, sailfish, or oarfish and need to produce gene-level count matrices,…
Use when after peak detection and clustering have been completed on aligned and baseline-corrected GC-IMS data, and before imputation or statistical analysis.
Use when when applying Scanpy preprocessing functions (e.g., pp.normalize_total, pp.pca) to AnnData objects where the expression matrix X is backed by a dask.array.Array, you need…
Use when you have a raw peak-picked untargeted LC-MS dataframe with columns containing mass-to-charge (m/z), retention time (rt), feature identifiers, adduct annotations, and…
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…
Use when you have a chromVARDeviations object with precomputed bias-corrected deviations and z-scores for multiple annotation sets (e.
Use when you have a detected LC-MS feature table (with m/z, retention time, and intensity columns) and need to identify which features are derivatives of the same parent molecule…
Use when you have training LC-HRMS chromatograms (rt × m/z matrix format) from which you have already extracted peak candidates using smoothing and gradient-descent peak…
Use when you have applied two different clustering or dendrogram-flattening methods (e.g., constant-threshold vs.
Use when when validating a new or reimplemented quantification tool against a reference implementation on the same dataset and index, or when investigating whether changes to seed…
Use when you have paired scATAC-seq peak matrices and scRNA-seq gene expression matrices from the same cells (multiome data) and need to perform joint clustering, visualization,…
Use when your input is a normalized, centered gene expression matrix with many genes (e.g., 12,000+) and you need to validate whether reducing to a smaller number of principal…
Use when after feature detection and alignment on raw MS data, when you have a list of unknown feature m/z values and need to assign them to known xenobiotic metabolites or their…
Use when you have positive- or negative-mode tunemix reference data (with known CCS values, m/z, and measured drift times) and need to establish a calibration model for converting…
Use when your LC-MS peak table from MS-DIAL or similar software contains data from multiple ionization modes (positive and/or negative) and/or multiple chromatographic columns (e.
Use when preprocessing raw Agilent MassHunter (.d) or UIMF IM-MS data files that exhibit signal saturation—ion intensity clipping caused by detector or amplifier limits—which…
Use when you have received paired .imzML (XML metadata) and .ibd (binary data) files from an Imaging Mass Spectrometry instrument and need to discover the imaging geometry, m/z…
Use when you have observed metabolites (from LC-MS/MS, chromatography, or spectroscopy) whose identities are unknown, and you wish to constrain the candidate pool by leveraging…
Use when after training a decision tree classifier on ChemEcho sparse feature vectors (representing tandem mass spectra fragmentation patterns), especially when the goal is to…
Use when when you have loaded a cooler file containing Hi-C contact matrices and need to quantify how contact probability decays with genomic distance within a single chromosome.