Use when you have raw Hi-C FASTQ files from a Hi-C wet-lab protocol and need to convert them into processed Hi-C contact maps (.hic files) for loop detection, TAD identification,…
Use when raw Agilent MassHunter (.d) or UIMF mass spectrometry files exhibit jagged or noisy peaks, particularly for low-abundance ions where signal-to-noise ratio is poor.
Use when you have a trained GNN model for molecular property prediction (such as CCS) and need to understand which atomic and bond features are most influential in driving…
Use when after loading raw metabolomics data (e.g., from Metabolon, Nightingale,
Use when you have transcript-level abundance estimates (from Salmon, kallisto, or similar) and a set of defined alternative splicing events (in ioe or ioi format), and you need to…
Use when after retention-time-based and abundance-correlation-based feature grouping have produced composite feature groups, and you need to identify which features within a group…
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 after constructing initial data bins from mzTree (indexed by int(mz × 1000)), determine whether a single bin contains one or multiple mass tracks.
Use when after anchor feature pairs (m/z and retention time values) have been selected from two disparately-acquired LC-MS datasets, and you need to correct for systematic…
Use when you have preprocessed MS/MS spectral data (converted to bag-of-fragments
Use when you have untargeted metabolomics mass spectrometry data (MS2 spectra with m/z values and intensities) and an existing knowledge-driven metabolite network, and you need to…
Use when you have ranked GCF-MF (Gene Cluster Family–Molecular Family) links using two or more independent scoring functions and a set of experimentally validated links.
Use when when you have imzML mass spectrometry imaging data files and need to convert raw ion image intensities into quantitative lipid abundance (pmol/mm²) using known internal…
Use when a user submits one or more MS/MS spectra (via .mgf file, USI list, or direct upload) and the downstream analysis requires dispatching to a specific domain-specific MASST…
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 when benchmarking or validating a pathway analysis method (such as PALS, ORA, or GSEA) on metabolomics data, you need quantitative evidence that the method's pathway…
Use when when processing raw or aggregated mass spectra datasets (from .mgf, .msp, .json, or .
Use when you have transcript-level quantification output files (e.g., quant.sf from salmon, abundance.
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 have raw tandem mass spectra data (mz/intensity pairs and precursor m/z values) and need to train interpretable machine learning models (regression or tree-based)…
Use when you have a feature table with assigned biomolecular class labels (e.g., from preceding class assignment step) and raw ion mobility arrival time measurements from TWIM-MS…
Use when after peak detection on a composite mass track has identified candidate peaks in a mass chromatogram, and before compiling the final feature table.
Use when you have a collection of preprocessed tandem mass spectra (binned into 10,000 equally-sized m/z bins, intensities square-root transformed, top 1,000 peaks retained), a…
Use when you need to confirm that a documented web service URL is live and reachable before attempting to submit analysis jobs, download results, or integrate the service into an…
Use when you have preprocessed, normalized beta-value matrices from EPIC or 450k methylation arrays with at least two sample groups (case/control, treatment/untreated, or similar…
Use when after peak picking and sample alignment when you have an aligned feature table containing m/z and retention time coordinates.
Use when you have centroided MS2 spectra (in mzML format from data-dependent acquisition) and a list of known or suspect PFAS diagnostic fragment masses, and you need to…
Use when after loading a feature table with m/z values from MS-Dial output when you need to identify and remove features with anomalous decimal m/z values.
Use when after feature extraction and peak recognition have produced detected MS/MS spectra (precursor m/z, charge, retention time, and fragment ion peaks), and you need to export…
Use when when you have vendor mass spectrometry raw files (e.g., .raw format) that must be converted to an open format (Aird) using a Windows .
Use when ingesting or validating project JSON documents against a schema (such as app/public/schema.json in the Pairing Omics Data Platform) that designates certain fields as URL…
Use when when you have a large MsBackend object and need to (1) select a contiguous or non-contiguous range of spectra for focused analysis, or (2) combine spectra from multiple…
Use when you have raw LC-MS/MS chromatogram files in mzML/mzXML format (converted from Thermo, Waters, or Bruker instruments) acquired in DDA or targeted MS/MS mode, and you need…
Use when when deploying a Shiny application with mixed R and Python dependencies
Use when you have raw MS intensity data paired with known-concentration calibration standard measurements, and you need to convert intensities to absolute or relative…
Use when you have raw mass spectrometry data in vendor-proprietary formats (e.g., .raw, .d, .ms) that you need to upload to MassIVE for public sharing or submit to GNPS for…
Use when apply this filter after feature detection and before downstream statistical analysis when your experimental design includes blank samples (e.
Use when after instantiating a transformer encoder module for mass spectrometry data processing (e.g., in IDSL_MINT), before training on large MS/MS datasets or running inference…
Use when you have a trained graph neural network model for CCS prediction and need to identify which molecular structural features drive individual predictions or systematic…
Use when when you have m/z values from spatially-resolved mass spectrometry imaging (MSI) and need to predict their molecular formulae with high precision.
Use when you have raw .idat files or beta-valued matrices from Illumina HumanMethylation450 (450K) or EPIC array experiments and need to import them into R for quality control and…
Use when you have raw electron ionization mass spectra (m/z and intensity pairs) that you intend to match against a library using the Identity (EI Normal) or Similarity (EI…
Use when when you have predicted MS/MS fragments from quantum chemistry calculations on N-Me derived unsaturated sterol structures and need to map each fragment to its precursor…
Use when you have a trained binary molecular classifier (like BitterPredict) and want to understand which groups of chemical descriptors drive its predictions.
Use when you have a peak table from tandem MS preprocessing (e.g., MS-DIAL, Metaboscape) and suspect that isotopic patterns have been incorrectly split during feature detection.
Use when you have access to the source code of a webservice component (Python, configuration files, route definitions) and need to produce machine-readable API documentation…
Use when when a user has prepared a custom collection of metabolite sets (e.g., from spectral fragmentation clustering, literature curation, or domain-specific grouping) in CSV or…
Use when you have raw mzML files and feature tables (CSV from mzMine or XCMS) for LCMS data, have generated training/validation/test batches with known class imbalance, and need…
Use when you are implementing a custom MsBackend subclass for the Spectra package and need to ensure that spectraData() returns all core spectra variables (e.g., centroided,…
Use when when you have encoded spectral features (from a CNN featurizer applied to 1D 1H and/or 13C NMR spectra) and a set of candidate molecular fragments predicted for a…
Use when you have mass spectral libraries from multiple sources (e.g., NIST EI, RIKEN MS2, MoNA GC-MS or LC-MS/MS, GNPS mgf) that need to be consolidated for use in MS-DIAL, or…
Use when after identifying structural clusters (isotopologue groups, adduct groups, and cross-assay links) and assigning features to correlation clusters via hierarchical…
Use when you have implemented or are validating a reader/writer library for a mass spectrometry file format (such as mzPeak, mzML, or similar), and need to confirm that data…
Use when after generating raw Hi-C contact matrices from aligned reads (post-merge, pre-analysis).
Use when when converting tabular data to JSON via the matrix directive, you need to exclude records that fail domain-specific validation (e.g., only retain records where a 'test'…
Use when when you have a new or updated R package available via a non-CRAN repository (such as r-universe) and need to verify it installs cleanly, passes R-CMD-check compliance,…
Use when you are building or refactoring a scientific Python library and need to decide how to organize and expose utility functions (e.g., adaptive coarse-graining, filtering,…
Use when you have a GC-MS dataset in CSV format with retention times, base peak m/z values, component areas, and compound names, and you need to identify whether specific query…
Use when when you have deposited a collection of JSON project documents in a platform and need to verify that all conform to the published schema before public release or — from…
Use when at the start of an untargeted LC-MS annotation pipeline when you have a KEGG database with exact masses and need to prepare a mass-matching reference.