Use when you have a raw peak-intensity matrix from untargeted LC-MS data (organized as rows=peaks, columns=samples) and need to generate initial candidate metabolite assignments.
Use when when you have tandem mass spectra (MSMS) from related or candidate molecules and need to determine which similarity metric—cosine, modified cosine, or neutral loss— ranks…
Use when you have imaging mass spectrometry (IMS) datasets with peak intensity features organized as spatial graphs (nodes = pixels/voxels, edges = spatial adjacency), and you…
Use when when you need to verify or retrieve package-internal metadata about compiled .NET assembly location and version before processing raw mass spectrometry files, or when…
Use when you have extracted tabular data into an intermediate JSON form and need to restructure records by mapping input fields to output dictionary keys, collating multiple…
Use when you have raw or processed TWIM-MS data (arrival time and m/z pairs) from multiple lipid, protein, or metabolite classes and need to classify features by biomolecular type…
Use when you need to map computed per-bin metrics (insulation scores, boundary calls, contact frequencies) back to genomic coordinates for export to BED/GFF format,…
Use when you have vendor-independent centroided mzML files from LC- or GC-HRMS data acquired in data-dependent acquisition (ddMS2) mode and need to extract detected features with…
Use when you have received raw CE-MS or LC-MS output files in vendor-specific formats from a mass spectrometry instrument and need to process them through an untargeted…
Use when you have loaded fragment data from single-cell ATAC-seq experiments into a backed AnnData object (with fragments stored in .obsm['fragment_paired'] or .
Use when you have multiple CSV feature tables from independent metabolomic experiments, each with RT and m/z annotations, and you need to produce a single consolidated feature…
Use when you have isotope-corrected or raw ion-image intensity matrices from LipidQMap or similar MSI software and need to: (1) export them as persistent HDF5 containers for…
Use when when a user submits one or more MS/MS spectra and has declared or implied a domain context (microbial, plant, tissue, microbiome, food, or metadata aggregation), and the…
Use when when designing injection plate layouts in InjectionDesign and needing to display sample positions with clear, domain-appropriate labels on the y-axis (e.g., row…
Use when you have raw GCxGC-MS chromatogram data in NetCDF (CDF) format from an instrument and need to load it into R for preprocessing (smoothing, baseline correction, peak…
Use when after log-transformation and missing-value imputation of a metabolomics
Use when after training a neural network or regression model to predict metabolomic profiles from microbiome data.
Use when when you have pairs of MS/MS spectra (in mgf, msp, mzml, mzxml, json, or usi format) and need to retrieve structurally related compounds or rank spectral similarity on a…
Use when you have acquired EI or MS/MS spectral libraries from multiple public sources (NIST, RIKEN, MoNA, SWGDRUG, GNPS) with inconsistent metadata field layouts, missing or…
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 trained NeatMS neural network model (.h5 format) and need to select an operating threshold for peak classification on your LCMS dataset.
Use when when you have raw or centroid-mode LC-MS All-ion fragmentation (AIF) spectra and need to generate or match against ion fragment databases.
Use when you have a feature table from LC- or GC-HRMS data (either detected via pyOpenMS or imported as a custom feature list) containing m/z, retention time, and intensity…
Use when when you have a large collection of reference MS/MS spectra (spectral library) and need to search unknown query spectra against it rapidly, particularly for open…
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 need to quantify the degree of match between two MS/MS spectra—either
Use when you have peak-abundance data (after molecular formula assignment, peak filtering by m/z, isotope, ppm error, and sample presence thresholds) and you need to quantify and…
Use when you have NMR metabolomics measurements paired with pre-analytical metadata (processing delay times, centrifugation timing, sample type such as plasma vs.
Use when after preprocessing, imputation, and batch correction of LC-MS peak tables when you need to group redundant or related feature measurements (e.g., [M+H]+ and [M+Na]+…
Use when after generating a frequency count table (e.g., from count_fold_changes
Use when you have a collection of MS/MS spectra (in mzML or MGF format) from a proteomics experiment and need to group or retrieve spectra derived from the same peptide without…
Use when when you have two independent predictions of categorical outcomes (up/down/no-change variation signs) across multiple sample pairs and need to measure agreement beyond…
Use when when reading mzPeak files or other Parquet-backed mass spectrometry archives where spectral m/z and intensity arrays are stored in columnar layouts (point or chunked…
Use when after calculating differential methylation across samples using calculateDiffMeth(), when you need to separately enumerate and extract hyper-methylated (increased…
Use when when a statistical method offers a parameter to trade computational cost for precision (e.
Use when after componentization of parent and TP features with generateComponents(algorithm='tp'),
Use when when you have generated multiple 3D conformations for a molecule or set of ionized adducts (e.g., via RDKit) and need to retain only the most energetically favorable…
Use when you have a collection of tandem mass spectrometry spectra in mzML or similar format and need to prepare them for LDA-based motif discovery.
Use when when you have an LC-MS feature table with m/z and retention time columns and need to identify which observed ions correspond to the same neutral compound under different…
Use when importing MS/MS spectral libraries (particularly from MoNA or GNPS) where SMILES or chemical structure identifiers are embedded in free-text or non-standard Comment…
Use when after completing feature annotation with the annotateRC function on LC–MS All-ion fragmentation (AIF) datasets, when you need to persist ranked metabolite candidates,…
Use when when processing multiple centroided mzML LC-MS files from the same study and you need to identify which mass tracks represent the same metabolite across samples.
Use when you have a pre-trained deep learning encoder (e.g., TCN spectrum encoder trained on a large corpus) and want to adapt it to a new task (e.
Use when after completing the MS2LDA LDA modeling step when you have a JSON-serialized inferred motifset (Mass2Motifs with fragment and neutral-loss patterns) and need to annotate…
Use when you have raw or baseline-corrected metabolite abundance measurements from mass spectrometry and need to prepare them for batch effect correction (e.g., CordBat) or…
Use when you need to create realistic, diverse chemical populations for simulating LC-MS/MS acquisition strategies in a virtual environment.
Use when after theoretical spectra have been generated for lipid–adduct combinations with enumerated fragment masses and intensities, and you need to deploy them for downstream…
Use when after generating a Chemical Feature Tree artifact (Phylogeny[Rooted]) from q2-qemistree's make-hierarchy method, or when importing a tree from external sources, to…
Use when you have raw quantification data (abundance or intensity values across samples and features) from mass spectrometry or similar high-dimensional assays and need to prepare…
Use when after completing PCA and k-nearest neighbor graph construction on preprocessed, log-normalized, highly-variable-gene-filtered single-cell RNA-seq data (stored in an…
Use when when you have lipidomics quantitation data (lipid abundances across samples) that you need to load into a unified, annotated R object for analysis—either from public…
Use when when you have a list of chemical compounds (with m/z values, retention times, and intensities) and need to simulate their acquisition behavior under a specific ionization…
Use when after batch correction of a metabolomics dataset using pooled study quality control (SQC) samples, when you have multiple candidate internal standards and need to…
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 you have molecular structures encoded as SMILES strings and need to incorporate them into a multi-modal language model (such as BART) that also processes mass…
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 after chromatographic peak detection and feature detection in LC-MS preprocessing, when you have a set of detected features (m/z, retention time, intensity) and need to…
Use when you have TWIM-MS data (arrival time and m/z values) from a multi-omic sample and need to: (1) establish a CCS calibration curve from known standards, (2) assign…
Use when you have received a conda/pip requirements file (e.g., jestr_requirements.txt)
Use when when exporting quantified ion images and pixel metadata from LipidQMap to HDF5 format for use in downstream Cardinal or other MSI analysis workflows.