Use when when you have raw mass spectrometry data (from mzML, Bruker .d, or CSV format) loaded into a Pandas DataFrame and need to ensure it has the correct column structure (m/z,…
Use when you have a characterized lipid species (with defined class and fatty acid composition) and need to predict which adduct forms will ionize under your experimental…
Use when you have fitted an MB-PLS model on multi-assay LC-MS intensity data (e.g., HPOS, LPOS, LNEG), computed MB-VIP scores for all features, and need to identify which features…
Use when you have (1) genomic data from a Streptomyces or other RiPP-producing organism in raw FASTA format or annotated GenBank format, (2) high-resolution LC-MS/MS spectra in…
Use when you have DDA LC-MS/MS raw data (mzML format) with detected chromatographic
Use when when you have raw mass-spectrometry data (precursor m/z, ionization mode, and fragment m/z–intensity pairs) that must be fed into a CNN model for metabolite annotation…
Use when you have centroided mzML files from LC–MS experiments and need to perform targeted metabolomics or lipidomics analysis.
Use when when you have generated a scan index from rawrr::readIndex() on a Thermo .
Use when when preprocessing a heterogeneous spectral library (e.g., GNPS public library) that contains spectra from multiple instrument types, and you need to partition data by a…
Use when you need to support multiple plotting backends for the same data visualization task, and you want to centralize backend selection logic so that users can specify their…
Use when you have raw or processed HRMS/MS data from Q-Exactive, Agilent Q-TOF, Bruker Q-TOF, or SCIEX Q-TOF instruments in formats such as mzML, CSV peaklists, or vendor-specific…
Use when when you have processed metabolomics LC-MS/MS data organized by batch and sample type (including pooled QC replicates), and you need to quantify whether batch-to-batch…
Use when when deploying a complex bioinformatics pipeline (e.g., HiC-Pro) that depends on multiple external tools with version constraints (samtools ≥1.9, bowtie2, R packages,…
Use when you have precomputed expected contact frequency tables (TSV format with columns like dist_bp, contact_frequency, n_valid) and need to apply log-binning and smoothing to…
Use when when you need to reproduce a computational workflow described in a GitHub repository, validate CI/CD pipeline definitions (e.g., GitHub Actions workflows), inspect source…
Use when when evaluating whether an MS data processing platform (such as mzmine) supports the full range of separation/ionization techniques your laboratory uses, or when…
Use when when implementing or refactoring a FileInterface._open method or similar polymorphic dispatcher that conditionally instantiates different handler classes based on file…
Use when you have mass spectrometry run data (spectra, chromatograms, instrument metadata) that must be stored in or recovered from the mzPeak format, or when you need to validate…
Use when after running inference on test mass spectrometry spectra with a trained deep learning model (e.g., PS2MS) to verify that class label predictions and confidence scores…
Use when when setting up a multi-stage bioinformatics workflow (e.g., ENPKG) that calls external tools (MZmine, Sirius, SPARQL engines) and depends on specific Python libraries;…
Use when when you have DDA LC-MS/MS data (mzML format) with identified chromatographic peaks at a specific m/z (e.g., 304.1131) and multiple MS2 spectra fragmented from that…
Use when when a Python package provides optional support for specialized data formats or functionality (e.
Use when validating project JSON documents against the platform's schema (app/public/schema.json) and you need to ensure all URL-type fields conform to URL syntax rules.
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 you have executed batch searches of MS/MS spectra against multiple domain-specific MASST tools and need to synthesize results across domains (e.
Use when when you have two or more implementations of a spectral search tool (e.g., MASST vs. MASST+) and need to quantify whether claimed performance improvements (e.g.,…
Use when when you have a Thermo Fisher Scientific Orbitrap .raw file and need to confirm that a targeted acquisition method (e.g., PRM targeting a specific precursor m/z) is…
Use when when processing untargeted LC-MS metabolomics data with XCMS and need to identify low-quality peak integrations that may introduce noise or bias into subsequent compound…
Use when you have an experimental mass spectrum (query) and a set of molecular candidate structures, and you need to rank the candidates by how well their predicted spectral…
Use when you have raw or preprocessed electron ionization (EI) mass spectral data that must be stored in, retrieved from, or validated against the MSP file format (used by NIST MS…
Use when you have access to both raw data (deposited in a repository like Zenodo) and analysis scripts (in a GitHub repository), and you need to confirm that the published…
Use when after executing a MassQL query that returns a tabulated results DataFrame (e.g., MS1 or MS2 scan metadata, peak intensities, retention times), and you need to produce…
Use when your spatial metabolomics dataset contains raw m/z features (e.g., from MALDI-MS imaging or LC-MS/MS) without metabolite annotations, and you have selected a reference…
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 have a log2-normalized, zero-mean, unit-variance intensity matrix (rows=metabolites, columns=samples) and a curated metabolite set database (e.
Use when you have completed a ViMMS simulation run or processed real LC-MS/MS data and need to quantitatively assess whether one DDA controller (e.g., WeightedDEWController with…
Use when when implementing a custom MsBackend and the spectraData() method needs to return all core spectra variables (e.g., centroided, polarity, collisionEnergy) regardless of…
Use when when implementing a custom MsBackend subclass and need to verify that spectra variables (e.g., precursor m/z, retention time, MS level) conform to expected data types…
Use when you have raw mass spectrometry spectra (peak lists or intensity arrays) that must be fed into a pre-trained deep learning model for substance classification (e.g., PS²MS…
Use when your input is a SummarizedExperiment containing multiple batches or injection sequences of metabolomics samples (study samples, QC replicates, calibration lines) with…
Use when you have high-resolution MS/MS spectra in mzML, mzXML, or MGF format and need to cluster or search across millions of spectra.
Use when when you need to simulate LC-MS/MS data for fragmentation strategy development and do not have (or wish to augment) real experimental chromatograms.
Use when when you have a collection of N-Me derivatized unsaturated sterol structures from tissue samples or standards that must be fed into MS/MS fragmentation prediction or…
Use when when you have trained a candidate model (e.g., an ensemble, a new architecture) and need to demonstrate its advantage over published or reference implementations on the…
Use when you have raw .idat files or a beta-valued matrix from an Illumina HumanMethylation450 or EPIC array experiment and need to import the full probe set into R for downstream…
Use when after XCMS feature detection, grouping, retention time correction, and missing value filling have produced an aligned feature matrix, when you need to group features…
Use when you are converting a processed Cardinal MSImagingExperiment object (containing normalized peaks, optional spatial shrunken centroids segmentation, and feature m/z…
Use when you have a set of in silico-predicted compounds (with SMILES structures) and an experimental metabolomics peak list (m/z values), and you need to filter predictions to…
Use when you have single-cell RNA-seq count matrices or processed expression data and need to store them alongside cluster assignments (e.g., leiden cluster labels), cell…
Use when when you need to evaluate GNN performance on collision cross section prediction using the enveda/ccs-prediction repository, either by loading an existing pre-trained…
Use when after isotope detection has enumerated C13 isotopologue patterns across m/z, drift time, and retention time dimensions, and you need to reduce false positives by…
Use when you have an untargeted metabolomics feature table (m/z, retention time, p-value from statistical test) but lack comprehensive metabolite identifications or MS/MS…
Use when when you have loaded a dataset of molecular fingerprint vectors (such as biosynfoni fingerprints from a Zenodo deposit) and need to quantify how sparse the…
Use when working with raw FT-ICR transient data (e.g., ESI_NEG_SRFA.d format) prior to noise thresholding and mass-domain calibration.
Use when when you need to benchmark multiple encoder types (e.g., FFN vs. GNN) on the same predictive task and require evidence that performance differences reflect genuine…
Use when you have paired-end or single-end RNA-seq reads (FASTQ format) and a reference transcriptome (FASTA), and you need to estimate transcript-level abundances (NumReads and…
Use when after you have partitioned a feature network into connected subnetworks (each containing ion features linked by isotope or adduct mass differences).
Use when you have raw peak tables exported from a tandem mass spectrometry preprocessing tool (e.g. Progenesis, MS-DIAL, or Bruker Metaboscape) and need to integrate them with…
Use when you have one or more mzML files (XML-based mass spectrometry data) and need to convert them into mzPeak format for downstream analysis, archival, or integration with…
Use when after constructing a MetaboSet object with LC-MS peak abundances, sample metadata (pData with QC labels), and feature metadata (fData), and after marking missing values…