Use when you have paired ChIP and control BED/BEDPE files and need to account for local sequencing bias before peak calling.
Use when when building Word2Vec or embedding-based spectral similarity models where you need to capture fragmentation patterns beyond individual peak positions.
Use when when you have mass spectrometry raw data (DI-MS or ASAP-MS format) from plant samples that are easily confused due to morphological similarity, or when you need to verify…
Use when after loading raw Agilent Unknowns Analysis CSV output and when you need to convert tentative compound identifications (matched only by GC-MS library cosine similarity or…
Use when you have DDA LC-MS/MS raw data (mzML format) with detected chromatographic
Use when you have tandem mass spectra for compounds with known binary or categorical molecular properties (e.
Use when when you have peripheral blood sample cohorts (plasma/serum) with multiple timestamps (e.
Use when after retrieving a JSON or tabular response from a web service endpoint (such as CANOPUS), validate the result before parsing or integrating it into your analysis…
Use when when you have processed Cardinal MSI data (normalized peak intensities,
Use when you have an unknown MS/MS spectrum (tandem mass spectrum) with a measured precursor m/z and fragment peaks, and you need to assign the most likely molecular formula and…
Use when you have a GNPS mass spectral molecular network (classical or feature-based) and MS2LDA-derived Mass2Motif data, and you need to annotate network nodes with both chemical…
Use when when ingesting mass spectral libraries (EI or MS2) where SMILES information is embedded in the Comment field rather than in a dedicated SMILES metadata field—particularly…
Use when you have training LC-HRMS chromatograms (rt × m/z matrix format) from which you have already extracted peak candidates using smoothing and gradient-descent peak…
Use when developing or reviewing Python code for a scientific package (e.g., cooltools) that targets collaborative development with multiple contributors.
Use when you have .mzML or .abf LC-HRMS metabolomics raw data files and need to perform peak detection, feature identification, and chromatogram alignment reproducibly across…
Use when after selecting statistically significant features from multi-assay LC-MS metabolomics datasets (e.g., via MB-VIP and permutation testing with p < 0.01).
Use when you have paired spectrum-compound reference data and need to simultaneously retrieve candidate compounds rapidly (bi-encoder) while also refining relevance scores through…
Use when you have a metabolomics dataset with left-censored missing values (e.g., below limit of quantification in LC/MS or GC/MS) and need to evaluate multiple imputation…
Use when after peak picking and alignment have been performed on MSImagingArrays
Use when you are receiving molecular structures from external sources (COCONUT database, ZINC database, user-provided chemical data) in varying formats (SMILES strings, InChI…
Use when when you have generated a set of predicted metabolite structures from BioTransformer's metabolism prediction engine and need to assign identity to observed compounds from…
Use when your IM-MS lipidomics samples have been spiked with fully labeled isotopic internal standards (e.
Use when you have an experimental mass spectrum (or a set of spectra from LC-MS/MS data) and need to identify the underlying metabolite(s) by comparing against known reference…
Use when you have a list of candidate metabolites for an unknown compound (from mass-to-structure search or library matching), experimental retention time(s) from one or more…
Use when you need to run the Zamboni-lab Masster (MASSter) workflow for untargeted LC-MS metabolomics data analysis.
Use when when you have ionized adduct structures (in SMILES or MOL format) from an upstream ionization-state determination step and need to produce multiple low-energy 3D…
Use when after isotope correction has been applied to MSI ion images, when you have sprayed or identified a reference lipid standard of known amount (pmol/mm²) and need to…
Use when you have GC-MS data preprocessed into a structured spread format and need to confirm that a set of known or suspected compounds are correctly identified in your samples.
Use when you have a Sciex Multiquant TXT export file containing a metabolomics or lipidomics analytical sequence and need to locate QCpool samples that were injected at regular…
Use when when preparing MS/MS spectral data for training word-embedding models (Word2Vec, Skip-gram, CBOW) that will learn relationships between fragment ions and neutral losses.
Use when when you have cloned a Python package repository and need to prepare a working environment for development, debugging, or contribution.
Use when you have computed pairwise similarity or mass difference scores between all fragment ions across two tandem mass spectra and need to select the non-overlapping set of ion…
Use when when you have pre-processed MS/MS spectra and a pre-trained Word2Vec model, and need to compute fast, scalable similarity scores for library matching or molecular…
Use when when you have raw LC-MS chromatographic data (mzML or vendor format) and need to identify and characterize all detectable peaks across the full retention time range for…
Use when you have a large collection of MS/MS spectra (hundreds of thousands to millions) that need to be clustered, you have already constructed nearest neighbor indexes on…
Use when you have raw microbiome (e.g., 16S rRNA or metagenomic) or metabolomic count tables (samples × features) and plan to train predictive models (e.g., MiMeNet, linear…
Use when after calculating differential methylation across samples using calculateDiffMeth(), when you need to separately enumerate and extract hyper-methylated (increased…
Use when after MS-Dial peak picking and feature table construction, when you observe a high proportion of features with anomalous m/z decimal values that are inconsistent with…
Use when when you have SWATH-MS raw data (mzML or vendor format) containing multiplexed MS/MS spectra from multiple co-eluting precursor ions and need to separate these spectra…
Use when after loading centroided .mzML LC–MS runs and before executing full peak detection and integration.
Use when after loading a specXplore session data object file from the hard drive and instantiating a dashboard session layer with it, validate that the architecture layer has…
Use when you have a set of conformers that have already been filtered by ASE-ANI neural network potentials and need to extract quantum-mechanical electronic properties…
Use when you have extracted mass tracks (EICs) from multiple LC-MS samples aligned into a MassGrid structure, and you need to combine their intensity vectors into a single…
Use when after sample alignment and isotopologue/adduct grouping are complete, when you need to associate MS2 spectral data (DDA-acquired) with the consolidated feature groups to…
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 a collection of cleaned MS/MS spectra (in formats like mzML, mgf, msp, mzxml, or json) and need to predict molecular structural similarities between spectrum…
Use when when you have a pre-trained GNN checkpoint and a smaller, task-specific
Use when you need to understand or validate whether calling filter_mispicked_ions() (or similar R6 filter methods) with different copy_object settings will mutate your original…
Use when you have raw GC–MS or LC–MS data in two-dimensional m/z vs retention time format and need to identify marker features at parts-per-billion sensitivity without relying on…
Use when when you have obtained an R-based bioinformatic program (such as DNMS2Purifier.
Use when you receive a JSON response from a REST API endpoint (e.g., TensorFlow Serving /model/metadata) and need to extract and validate specific fields such as model input…
Use when designing a metabolite annotation workflow that must simultaneously leverage established biochemical knowledge (pathway databases, reaction networks) and experimental…
Use when you have a feature table from LC-MS analysis (containing m/z, retention time, and intensity values) and need to identify which detected features represent the same…
Use when when you have mzPeak files (Parquet-based archives in uncompressed ZIP containers) or other PyArrow-compatible columnar formats containing mass spectrometry spectra, and…
Use when after constructing feature tensors encoding atom adjacency matrices, bond types, and chemical properties from canonical SMILES—and before feeding graphs into a GNN…
Use when you have experimental fragment m/z values from HRMS/MS instruments (Q-Exactive orbitrap, Q-TOF) in CSV or mzML-derived peaklist format, and need to match them against a…
Use when you have raw untargeted LC/MS data in open mzML or mzXML format and need to extract a quantified feature matrix (m/z and retention time coordinates with sample…
Use when after generating theoretical spin multiplets for individual metabolites via first-order or density-matrix NMR simulation, but before combining spectra or applying Fourier…
Use when you have developed a predictive model and need to compare its performance against established baselines (e.g., linear regression, Random Forest, Canonical Correlation…
Use when after batch correction of metabolomics data using pooled study quality control (SQC) samples and calculation of compound/internal standard ratios, when you need to decide…