Use when after completing Cardinal-based preprocessing (feature summarization, TIC normalization, peak processing, spatial segmentation, and SSC annotation), use this conversion…
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 1D NMR spectra (¹H or ¹³C or both) for an unknown organic compound with ≤19 heavy atoms and need to rapidly predict its molecular formula and connectivity graph…
Use when you have raw IMC (protein imaging) and SIMS (metabolite imaging) data from tissue regions that require spatial co-registration, single-cell-level intensity…
Use when you have raw Bruker NMR spectral data files (1D 1H format) stored in a directory structure and need to prepare them for automated metabolite identification and…
Use when when you have Thermo Fisher Scientific Orbitrap .raw files (e.g., from Q Exactive HF instruments) and need to extract spectral, chromatographic, or metadata directly into…
Use when investigating how a specific pull request (e.g., PR #72 introducing MS2Query''s two-branch workflow split) modified the codebase architecture, control flow, or data…
Use when when designing or optimizing S4-based data backends (such as MsBackend subclasses) and you need to decide whether to pre-populate all slots with complete data structures…
Use when after running ModiFinder's probability generation on a known compound–modified compound pair, you have a vector of per-atom modification probabilities and need to…
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 when loading or creating an NMR spectral dataset (Dataset.createDataFile)
Use when when you have processed LC-MS data through XCMS alignment but suspect misaligned features due to retention-time drift over long acquisition periods (>1 week) or large…
Use when when you have access to a research repository or README documenting a machine learning implementation (e.g., Keras/TensorFlow-based deep learning model) and need to…
Use when you have preprocessed metabolite intensity data (log2-transformed, zero-mean unit-variance standardized) mapped to compound annotations, and you need to derive activity…
Use when you have LC-MS/MS spectral data (in MGF, mzXML, mzML, or mzData format) and corresponding genomic sequence data (raw FASTA nucleotide sequences or genome mining tool…
Use when when you have a repository containing hundreds or thousands of structured records (e.g., MassBank records in standardized format) that must be validated for correctness…
Use when you have raw LC-MS/MS data acquired in Data-Dependent Acquisition (DDA) mode and need to create a labeled training dataset for customized purification model development.
Use when constructing or enriching a chemical formula database that must capture not just structural similarity (DBEdges) but also biological co-occurrence patterns.
Use when when you have just loaded the rawrr R package and need to confirm that the bundled .NET 8.0 assembly (rawrr.exe) is present and functional before performing any mass…
Use when building a transformer-based neural network for chemical formula ranking or classification from mass spectrometry spectra, and you need to encode categorical chemical…
Use when you have centroided mzML LC–MS data, a curated list of target compounds (with theoretical m/z, expected retention time, and polarity), and you need to confirm target…
Use when you have raw UPLC-HRMS data from ThermoFisher or Agilent instruments and need to feed it into MSThunder for nontargeted pollutant identification.
Use when you have a peak table from XCMS preprocessing with intensity measurements for the same set of metabolites across multiple QC replicate injections (samples marked…
Use when after BGC detection and clustering (producing GCFs) and metabolomics profiling (producing MFs with MS/MS spectra), when you have paired genomic and metabolomic data from…
Use when you are designing a new tool for FT-ICR MS analysis (or similar high-resolution mass spectrometry domain) and need to understand which analytical and visualization…
Use when after collecting observed separation efficiency scores at sampled gradient conditions and you need to propose the next gradient to evaluate.
Use when you have a list of query chemicals (compound names or SMILES) and a reference library organized by chemical groups (e.g., Types A–E, GroupA/GroupB), and you need to…
Use when you have raw MS2 spectra from a sample and need to collapse them into a single sample-level representation for comparison across multiple samples, particularly when…
Use when after generating collision cross section predictions on a validation or test set using a trained graph neural network model, and you need to quantify prediction accuracy…
Use when after completing Part 4 (Identification of ISF Features) in the ISFrag workflow, when you have an analysis results object containing identified ISF features and need to…
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 after baseline correction (e.g., via asymmetric least squares) when raw GCxGC-MS chromatograms still contain high-frequency noise that obscures true signal structure.
Use when immediately after importing raw peak tables and metadata from MS preprocessing software (e.g., Progenesis, MS-DIAL, Bruker Metaboscape).
Use when when implementing or auditing a data replacement method (e.g., `mz<-`, `intensity<-`) in an MsBackend subclass that must enforce ordering or format constraints on peak…
Use when you have generated a peak table or feature list from MZmine, XCMS, MS-DIAL, or Compound Discoverer in its native export format and need to ingest it into LipidMa — from…
Use when you have statistically significant features from multiple LC-MS assays with different ionization modes (e.g., positive and negative ESI) and need to collapse redundant…
Use when after composite-map peak detection (scipy.signal.find_peaks) has identified candidate peaks on aligned mass tracks, but before compiling the final feature table.
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 collection of tandem mass spectrometry spectra in mzML or similar format and need to prepare them for LDA-based motif discovery.
Use when after MS2Deepscore has selected the top 2000 candidate spectra from a library based on spectral similarity, and you need to re-rank these candidates to surface the single…
Use when during MSP, MGF, JSON, or CSV file parsing when standardizing mass spectra from heterogeneous open mass spectral libraries (OMSLs).
Use when you have cloned a Python project (e.g., scverse/scanpy) that includes a hatch.toml configuration file and need to set up a consistent development or testing environment.
Use when you have a backed AnnData object containing processed fragment data (stored in .obsm['fragment_paired'] or .
Use when analyzing complex GC-MS mixtures where two or more chemical compounds elute at similar or identical retention times, producing overlapping or merged peaks in the raw…
Use when after running tardisPeaks() with screening_mode=TRUE on centroided .mzML LC-MS data, when you need to visually inspect whether the 10 target compounds (internal standards…
Use when after batch effect removal and sample integration, when you have a normalized feature-by-sample abundance matrix (finalData) with corresponding sample group labels…
Use when when you need to execute a multi-backend visualization library (e.g., pyOpenMS-Viz with matplotlib, Bokeh, and Plotly) and must measure or validate execution times,…
Use when when you have centroided .mzML LC–MS runs and a target list (compound ID, theoretical m/z, expected RT, polarity) but are uncertain whether your m/z and RT windows are…
Use when after generating mzPeak files from prototype implementations (Rust, Python, R, or .NET) or after format conversion, and before integrating files into a mass spectrometry…
Use when when processing raw chromatography–mass spectrometry data (GC–MS or LC–MS) as a 2D m/z vs retention time map and you need to identify and visualize marker features for…
Use when you have extracted fragmentation patterns from a collection of MS/MS spectra (using mineMS2) and have partitioned spectra into components via GNPS molecular networking…
Use when you have a large collection of preprocessed MS/MS spectra (typically >10,000 spectra) with diverse chemical structures and you need to learn embeddings that capture…
Use when you have a collection of molecular structures (with SMILES strings, InChI, or similar identifiers) and corresponding experimentally determined or reference CCS values,…
Use when you have prepared metabolomics input files (feature quantification table, MS/MS spectra in MGF format, sample metadata) and are about to execute the TIMA taxonomically…
Use when when you have run differential methylation analysis in methylKit and need to validate whether overdispersion correction (overdispersion='MN') produces appropriately…
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 filtered peak or chromatin accessibility counts and need to annotate each peak with the presence or absence of specific DNA sequence patterns—either predefined…
Use when you need to verify the scope and completeness of a software platform's analytical capabilities—particularly when the project claims to support multiple input modalities…
Use when after serializing empirical compound collections to JSON format via khipu's build_empCpds command, or before ingesting empCpd.
Use when when preprocessing raw SMILES strings from external chemistry databases (e.g., CCSBase, METLIN-CCS, or custom compound libraries) that may contain multiple valid but…