Use when when you have an unknown compound's mass spectrum (m/z peaks and intensities in .mgf or equivalent format with mandatory PRECURSOR_MZ and IONMODE tags) and need — from…
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 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 large spectral libraries (thousands to millions of spectra) and need to search query spectra against them for peptide identification with tolerance for…
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 you have two spatial omics datasets (e.g., spatial transcriptome and metabolome spot matrices) collected from the same or adjacent tissue sections, with both feature…
Use when when you have spatial molecular data (e.g., Visium, imaging-based cytometry) stored in an AnnData object with coordinate information in .
Use when you have loaded an MS2 library (from NIST, GNPS, or other sources via read_lib()) that contains both positive and negative ionization modes mixed in a single file, and…
Use when apply PCA when you have a log-normalized, scaled gene expression matrix from highly variable genes and need to reduce dimensionality before constructing k-nearest…
Use when you have grouped unique 2D chemical structures by organism prevalence and need to confirm that the counts in each frequency bin (singleton, low-diversity,…
Use when when you have constructed a two-layer metabolite annotation network (knowledge-driven and data-driven) and need to propagate initial seed annotations (e.
Use when you have multiple MSP (mass spectrum) library files to read and merge in R, and your computational task is time-consuming (e.g., structure extraction, SMILES assignment,…
Use when you have xcms-processed LC-MS data with detected misaligned feature groups and need to recover the underlying raw retention time–intensity profiles for each feature and…
Use when when you have a set of molecules with known chemical structures and need to prepare them for classification or prediction tasks.
Use when after feature detection and alignment (XCMS or equivalent), when you have a CSV feature table with m/z and retention time columns and need to group features derived from…
Use when when you have a pre-trained encoder (e.g., TCN spectrum encoder in FIDDLE) that has learned useful representations on a source task (e.g., MS/MS spectrum encoding), and…
Use when when comparing mapping outputs between two selective-alignment implementations (e.g., C++ vs.
Use when you have a trained multitask model checkpoint and preprocessed spectral inputs (1D NMR spectra, 1H-only, 13C-only, or combined 1H+13C), and you need to generate…
Use when after scipy.signal.find_peaks has identified candidate peaks on a composite mass track segment, evaluate each peak to decide whether to retain it in the final feature…
Use when when you have computed PCA coordinates from chemical annotation matrices (e.
Use when when you have large sequential media files (mzML spectra, text chapters, or similar) and need to enable both random access by ID and sequential iteration without loading…
Use when you have deployed a microservice (e.g., TensorFlow Serving, REST API) and need to verify that specific endpoints (e.g., /model/metadata, /classify) return responses with…
Use when you have calibrated m/z peak lists, configured adduct transformations (e.g., [M+H]+, [M+Na]+, [M-H]−), and need to annotate peaks with molecular formulae from KEGG,…
Use when you have MS2 spectra data (MGF/mzML format) and aligned feature tables, and your analysis goal is to compare samples that may have poor MS1 feature overlap, strong…
Use when you have extracted peaks from multiple LC/HRMS batches (n > 500 samples across different analytical runs or days) and observe systematic retention time drift or offset…
Use when you have downloaded a GNPS archive from either GNPS1 (https://gnps.ucsd.edu) — from HolobiomicsLab/asb-skill-collections
Use when you have an untargeted metabolomics dataset with partial metabolite annotations (from database matching or prior curation) and need to extend annotation coverage to…
Use when when you have downloaded raw spectroscopic datasets from multiple sources (NMR, HSQC, COSY, IR files) and need to combine them into a single coherent training corpus…
Use when when you have mass spectrometry data stored in non-standard formats (SQLite, HDF5, custom binary) that pymzML does not natively support, and you want to enable…
Use when when you have both an observed NMR mixture spectrum and a candidate reconstructed spectrum (each represented as intensity distributions across chemical shift bins), and…
Use when you have a Thermo Fisher Orbitrap .raw file and need to retrieve a specific scan's spectral data (m/z and intensity arrays), validate instrument parameters (resolving…
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 when you have preprocessed 1H NMR spectral data with unidentified peaks and need to determine metabolite identity by exploiting the correlation structure of NMR signals.
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 preparing training batches for a neural network classifier on LCMS peak data where class counts are unequal (e.g., more high-quality peaks than low-quality peaks).
Use when you have loaded a collection of molecular fingerprint vectors (such as biosynfoni fingerprints from a deposited dataset) and need to characterize their statistical and…
Use when when you have a query electron ionization mass spectrum (as m/z and intensity pairs) and need to identify it against a spectral library stored in msp format.
Use when you have a USI string referencing a spectrum in an online public repository (PRIDE, MassIVE, etc.) and need to load its raw spectral data without downloading the entire…
Use when when reading a binary file format with a magic integer or fixed checksum field at a known offset, and endianness is not explicitly declared in file metadata or header…
Use when you have Thermo Orbitrap .raw files and need to access raw spectral data (individual MS1 or MS2 scans, base-peak values, chromatogram traces, retention times, or…
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 immediately after loading raw single-cell gene expression count matrices (AnnData objects) and before identifying highly variable genes or performing dimensionality…
Use when you have untargeted MS2 spectral data (in MS2MP-compatible format) and need to assign KEGG pathway annotations to unknown metabolites.
Use when when you have LC-MS/MS data in Mascot Generic Format (mgf) files and need to identify compounds against a curated custom database (e.g., prepared using CFM-id for a…
Use when your ChIP-Seq input is paired-end sequencing data stored in BEDPE format (e.g., CTCF_PE_ChIP_chr22_50k.bedpe.gz), and you need to estimate fragment length and call peaks…
Use when you need to verify that a QIIME 2 artifact (e.g., a Chemical Feature Tree from q2-qemistree, a FeatureTable[Frequency], or a Phylogeny[Rooted] object) has been correctly…
Use when after identifying precursor peptides from genome assemblies via BGC mining, when you need to enumerate the chemical space of PTM variants (lantibiotic, lassopeptide,…
Use when you have transcript-level quantification files (quant.sf, kallisto abundance.h5, or RSEM output) from one or more RNA-seq samples and need to construct a count matrix for…
Use when you have LC-HRMS profile-mode chromatograms with extracted local maxima exported as standardized 2D rt×mz areas, and you need to disambiguate true chromatographic peaks…
Use when augmenting mass spectrometry ion images for contrastive learning, specifically when you need to simulate the natural Poisson noise that arises from photon-counting…
Use when you have observed metabolites (from LC-MS/MS, chromatography, or spectroscopy) whose identities are unknown, and you wish to constrain the candidate pool by leveraging…
Use when when quantifying or mapping RNA-seq reads with salmon quant using the --writeMappings (-z) flag, or in any streaming output scenario where record count discrepancies…
Use when you have a tab-delimited feature table (m/z, retention time, intensities) from LC-MS preprocessing and need to group related ions (isotopologues, adducts, in-source…
Use when after forking and cloning a repository (e.g., scverse/scanpy) to verify that the development environment is correctly configured, or after implementing a feature or…
Use when after training a GNN-RT model on preprocessed molecular graph data (from Train.py) or after applying transfer learning to an in-house dataset (from Transferlearning.
Use when you have vendor-independent centroided mzML files from LC- or GC-HRMS data acquired in data-dependent acquisition (ddMS2) mode and need to extract detected features with…
Use when when you have discovered Mass2Motifs from MS2LDA topic modeling and need to automatically annotate them by finding the most structurally similar known spectra in a…
Use when you have positive- or negative-mode tunemix reference data (with known CCS values, m/z, and measured drift times) and need to establish a calibration model for converting…
Use when you have raw IM-MS data (Agilent MassHunter .d or UIMF format) and need to exclude early or late chromatographic regions—e.g., to skip dead volume, exclude blank runs,…
Use when when you have generated multiple 3D conformations for a molecule or set of ionized adducts (e.g., via RDKit) and need to retain only the most energetically favorable…