Use when you have preprocessed (smoothed and baseline-corrected) 2D-GCxGC-MS chromatograms from multiple samples and need to align their peak positions to a common reference…
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 retention-time and m/z-based peak alignment has been completed across a cohort of LC-MS samples, and you need to create a unified quantitative matrix for…
Use when when you have: (1) a collection of molecules represented as molecular graphs (nodes=atoms, edges=bonds with chirality/order attributes); (2) structured metadata…
Use when immediately after chromatographic peak detection (findChromPeaks) when you have detected peaks across multiple samples and need to identify which peaks represent the same…
Use when when you have MS/MS spectra with known chemical structures (InChIKeys or SMILES) and want to validate whether a novel or existing spectral similarity scoring method…
Use when when you have a Python package repository on GitHub and need to automatically verify that pull requests and commits pass unit tests and meet code quality standards before…
Use when you have .msp spectral library files with compound names but lack standardized chemical identifiers (SMILES, InChI, InChI Key, CAS number, IUPAC names, or molecular…
Use when when loading gene expression data (e.g., from GEO via getGEO or microarray ExpressionSet objects) that contains duplicate rows mapped to the same Gene ID, missing gene…
Use when after generating or filtering transformation products using generateTPs() or filter(), when you need to annotate MS/MS spectra using MetFrag and require a database of…
Use when when you need to validate that a .NET assembly (such as ThermoFisher.CommonCore.RawFileReader) is correctly installed and accessible before attempting data reading…
Use when when you have generated a set of candidate metabolites for a given experimental MS/MS spectrum and need to determine which candidate is most likely to be the true…
Use when when you have domain-specific functionality (e.g., spectral similarity scoring, peak detection algorithms) implemented in one language (Python) but need to make it…
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 when fitting a nonlinear retention time (RT) mapping spline to anchor feature pairs (m/z and RT values) from two LC-MS datasets acquired under different conditions, you…
Use when you have Sciex Multiquant (≥v3.0.3) TXT export files containing metabolomics or lipidomics analytical sequences that include pooled QC samples, and you need to verify…
Use when when you need to validate that MSI software (e.g., LipidQMap) achieves documented processing speeds on your target hardware, or when you need to establish a performance…
Use when after fitting a polynomial calibration model to tunemix reference data in DEIMoS, assess whether the model explains sufficient variance in the m/z–drift-time–CCS…
Use when when beginning mass alignment in a multi-sample LC-MS metabolomics study, before constructing the MassGrid.
Use when you have a fitted linear model (lmFit object) from microarray or RNA-seq count data and need to compute stable variance estimates and differential expression sta — from…
Use when after RAMClustR clustering and molecular weight inference via do.findmain, when you need to export deconvoluted cluster spectra for import into external annotation tools…
Use when you have raw GC-MS data (in netCDF or vendor format) containing overlapping chromatographic peaks from complex mixtures where individual compound spectra cannot be…
Use when after peak detection when you have a table of detected peaks with m/z values and retention times from LC/HRMS data, and you observe systematic m/z drift across a — from…
Use when after chromatographic peak detection on preprocessed LC-MS data, when you have detected features (peaks) in multiple samples and need to establish which peaks ac — from…
Use when you need to set up a cloned or downloaded scientific Python package for local development, testing, or execution.
Use when you have computed low-dimensional embeddings (e.g., t-SNE coordinates) or clusterings of mass spectra and need to validate that the learned representation space organizes…
Use when when integrating LC-MS/MS data from diverse sources (e.g., public repositories like MSV000080102, instrument outputs, or precomputed workflows) into NPDtools pipelines.
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 have trained multiple machine learning classifiers (e.g., AdaBoost, SVM, Random Forest) on the same metabolomics peak-quality training set using k-fold…
Use when you have mass spectrometry spectral data from multiple instrument types (e.g., direct infusion MS, ambient ionization MS, laser desorption/ionization MS) and need to…
Use when you have raw GC-MS output exported as CSV (containing columns: Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when when annotating large-scale untargeted metabolomics datasets where reference library coverage is incomplete and you need to infer metabolite identities for unannotated…
Use when you have (1) spatial omics data loaded in AnnData format with a pre-built spatial neighbor graph (from squidpy.gr.spatial_neighbors() or similar), (2) a categorical…
Use when you need to systematically enumerate all possible lipid species within a defined analytical scope—specifically when you have specified one or more lipid classes (e.g.,…
Use when when you have a metabolomics abundance table with missing values and need to decide which imputation method to apply, or when designing a simulation to evaluate…
Use when you have a feature-by-sample matrix (rows = annotated chemical features such as m/z, retention time, GNPS spectral library matches;
Use when after calculateDiffMeth() has been run on a methylBase object and you have a methylDiff object with q-values and methylation difference estimates.
Use when you have a trained NeatMS neural network model and labelled peak validation data, and need to select an operational classification threshold or understand how TPR and FPR…
Use when after implementing a neural network component that will feed into a downstream architecture (e.g., a transformer).
Use when when you have raw GC-MS output (CSV with columns: Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when you have raw or processed MS spectrum data (m/z and intensity pairs) from DI-MS, ASAP-MS, or other high-throughput mass spectrometry instruments that requires automated…
Use when you have completed batch spectral searches against multiple domain-specific MASST tools (via Fast Search API or individual domain searches) and need to combine and…
Use when preprocessing open mass spectrometry libraries (OMSLs) or aggregated spectral datasets where structural identifiers are inconsistently populated.
Use when after constructing a count matrix from transcript quantification files (via tximport, HTSeq, featureCounts, or direct alignment) and before running DESeq() differential…
Use when evaluating whether a published computational method can be independently executed: (1) source code is claimed to be available but repository structure, build…
Use when when deploying a Streamlit workflow app in offline mode (online_deployment:
Use when you have untargeted MS2 spectral data (from LC-MS/MS or similar instruments) and need to assign metabolic pathway context to detected compounds when standard spectral…
Use when you have imaging mass spectrometry data from spatial metabolomics experiments and need to reduce the high-dimensional peak space to a ranked set of marker ions for…
Use when after rMSIcleanup has classified ions as matrix-related or non-matrix, and you need to audit, validate, or communicate the annotation decisions.
Use when you have raw mass spectrometry spectra from an unknown analyte or a synthetic compound library and need to feed them into PS2MS or similar deep learning classifiers for…
Use when you have an mzML file (e.g. Manuels_customs_ids.mzML) with non-standard
Use when when ingesting heterogeneous MS spectral data from multiple open-access libraries (OMS libraries) where metadata completeness and correctness are uncertain.
Use when when you need to reverse-engineer or formally document the computational steps within a closed or under-documented scientific software module—particularly when the…
Use when after kNN imputation of metabolite measurements but before variance-stabilizing
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 you have RNA-seq read counts (FPKM or similar) for multiple cell lines or biological samples, a genome-scale metabolic model with GPR associations, and you need to…
Use when you have annotated metabolite structures (with SMILES strings) from a reference library (e.
Use when you have vendor-independent centroided mzML files from data-dependent acquisition (ddMS2) HRMS experiments and need to extract a reproducible feature list with mass,…
Use when a webservice component (like MAGMa's joblauncher) lacks formal API documentation but the source code is accessible, and downstream consumers (web applications, external…
Use when after applying pycombat-based batch correction to multi-batch interpolated feature tables in LC-MS metabolomics workflows, when you need to verify that batch effects have…