Use when extracting migration times of specific analyte or reference markers (e.g., Paracetamol EOF marker) from CE-MS files using peak-picking workflows.
Use when you have an experimental MS/MS spectrum (m/z and intensity pairs with known precursor m/z) and need to identify the compound by searching against public repositories or a…
Use when you have untargeted metabolomics data with unknown metabolite structures and need to generate plausible candidate products by systematically applying known enzymatic or…
Use when when you have a collection of molecular structures (as InChI strings, SMILES, or RDKit Mol objects) and need to feed them into a pretrained or transfer-learning neural…
Use when when you have raw GC–MS or LC–MS data (m/z vs retention time chromatography-mass spectrometry maps) and need to identify analyte signals and marker features without…
Use when you have raw CE-MS instrument output in mzML or netCDF format and need to extract specific ion traces (by m/z value), filter by effective mobility windows, or apply…
Use when when you have LC-IM-MS/MS data with measured collision cross section (CCS) values and m/z assignments, and you need to disambiguate sterol isomers (particularly N-Me…
Use when after frequency-based denoising has been applied to individual replicate spectra within each feature (via generate_denoised_spectra), you have a collection of denoised…
Use when when you have molecular structures, a regression target (e.g. retention time), and want to establish whether one class of molecular features (e.g., fingerprints)…
Use when you have paired mass spectra and molecular structure datasets and need to train a model that jointly understands both modalities for tasks like structure elucidation.
Use when converting JSON metadata and you need to populate a target field by selecting or iterating over records only when they satisfy a logical test condition (e.g., 'include…
Use when you have tunemix reference data acquired in both positive and negative ion modes and need to establish independent CCS calibration curves for each mode.
Use when you have loaded a raw or partially processed MsmsSpectrum object and need to reduce spectral noise before annotation, matching, or visualization.
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 when you have a mzPeak file (uncompressed ZIP archive containing Parquet tables) and need to access decoded spectral data arrays (m/z, intensity), spectrum metadata (scan…
Use when after submitting a POST request to the /api/smart3/search endpoint with peak data as a JSON payload, you receive an HTTP response and need to extract classification…
Use when when you have a metabolomics dataset loaded into a SummarizedExperiment
Use when when building or modifying an asynchronous annotation pipeline that dispatches metadata enrichment requests to multiple heterogeneous web services and must verify that…
Use when when you have extracted and concatenated MS/MS spectra from multiple replicates for a set of metabolomic features (stored in a preprocessed list), and need to apply…
Use when after mass tracks have been aligned across samples into a MassGrid structure (m/z-aligned, same mass-to-charge ratio) and retention time calibration dictionaries — from…
Use when when you need to inventory a collection of related web applications or tools distributed across multiple repositories, discover their live deployment URLs, trace their…
Use when when you need to understand how a Java application routes input data to processing modules based on declared data types, conditionally branches on instrument or format…
Use when you have (LC-)IM-MS lipidomics data from samples spiked with U13C labeled internal standards (e.g., fully labeled yeast extract) and need to quantify and correct…
Use when you have computed raw strain correlation scores (based on shared strain membership) between genomic and metabolomic objects of heterogeneous sizes, and you need to…
Use when you need to represent natural product molecules as fixed-length bit vectors for downstream machine learning (e.
Use when after fitting a linear model to expression data using limma's lmFit function on a design matrix encoding experimental groups, inspect the resulting MArrayLM object to…
Use when when executing peak integration on preprocessed GC-IMS data (after alignment and baseline correction) and you need to decide whether to include or exclude peaks that…
Use when when you have metabolomics results from multiple studies reporting compound identifiers, p-values, fold-changes, and study sizes (N), and you need to prepare them for…
Use when training embeddings from multi-modal spectral data (peak information + metadata) where you need to ensure both contrastive discriminability AND reconstruction fidelity.
Use when you have collected liquid chromatography (LC) spectra and retention time labels for your in-house molecular database, and you want to leverage a pretrained GNN-RT model…
Use when you have a GNPS mass spectral molecular network (in .graphml or Cytoscape format) and wish to annotate its nodes and edges with chemical class assignments from the GNPS…
Use when when you have TCN-predicted candidate formulas with ranked scores and need to train a Siamese rescore model to re-rank those candidates.
Use when after integrating transcriptomics-derived (RAS), metabolomics-derived (RPS), and extracellular flux constraints into cell-relative metabolic models, sample the feasible…
Use when when implementing fragment ion annotation in proteomics workflows and needing to determine whether neutral loss annotation (e.g., H2O: -18.010565, NH3: -17.026549) should…
Use when after LCMS feature alignment (e.g., Eclipse output) when you have a feature table with retention times and intensity profiles across multiple injections, and you need to…
Use when when preparing multi-formula MS/MS training data for a rescore model, if the raw positive examples show extreme imbalance (some formulas represented by hundreds of…
Use when after peak filtering (by m/z, isotopic presence, formula assignment error, and sample prevalence) and before multivariate analysis (PCA, NMDS, PERMANOVA) when comparing…
Use when at the start of any DaDIA pipeline execution, or whenever you are preparing to run a complex multi-package R workflow on a new system or after updating package managers.
Use when when compiling or maintaining a catalog of web-accessible scientific tools (e.
Use when performing untargeted metabolomics annotation (i.e., matching observed spectra to a compound database without a pre-defined target list) and you need to assign…
Use when when you have raw mass spectrometry spectral data in JSON format from open mass spectra libraries (OMSLs) or other sources and need to validate structural completeness,…
Use when you have LC/MS feature data (m/z, retention time, intensity) and need to assign metabolite annotations with confidence scores rather than binary peak-to-compound matches.
Use when you have aligned feature tables (CSV format) with corresponding MS2 spectra data (MGF or mzML files), and need to construct a sample-level vectorization matrix where each…
Use when you have (LC-)IM-MS lipidomics data from samples spiked with U13C-labeled yeast extract, measured CCS values for both labeled and unlabeled lipids, and need to quantify…
Use when you have NMR metabolite measurements from peripheral blood samples (plasma/serum) paired with processing delay metadata (pre-centrifugation and post-centrifugation times)…
Use when when you have detected peaks in a direct injection FTICR-MS mzML file (or similar high-resolution MS format) and need to assess whether m/z measurements are accurate and…
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 molecular descriptors or fingerprints for a set of compounds (e.g., from LC-MS metabolomics) and need to predict a continuous property—such as HPLC retention…
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 imported MSI data (imzML or vendor format) loaded into the napari plugin environment and need to organize raw spectral m/z and intensity arrays prior to…
Use when when importing a tab-delimited or Sciex OS text export metabolomics dataset into mzQuality, before building the SummarizedExperiment object.
Use when you have an unknown electron ionization (EI) mass spectrum and need to identify the compound by comparing it against a reference library (msp file format).
Use when you have execution-time metrics (from a benchmark table or profiling logs) across multiple visualization backends for the same set of plots (e.
Use when after feature detection and peak alignment have produced a feature table with zero or missing values across samples.
Use when you have paired-end RNA-seq reads (FASTQ) and a reference transcriptome (FASTA), and you need to estimate transcript-level expression (NumReads and TPM).
Use when after serializing empirical compound collections to JSON format via khipu's build_empCpds command, or before ingesting empCpd.
Use when you have a preprocessed bag-of-fragments corpus derived from tandem mass spectrometry spectra and need to discover recurring fragmentation motifs without prior compound…
Use when when you have ranked gene statistics and gene set collections, and your analysis requires P-value discrimination below a fixed lower bound (e.g., distinguishing between…
Use when you have LC-MS peak tables from parallel unlabeled and labeled (isotope-traced) sample cohorts, sample metadata defining groups and conditions, and you seek to identify…
Use when when you have aligned peak data from molecular networking (with m/z, intensity, retention time, and alignment quality metrics across multiple spectra) and need to…