Use when when you have a peptide sequence, MS2 fragment charge states, and a known isotope enrichment fraction (e.g., 1.
Use when you have two peak-picked, conventionally aligned LC-MS metabolomics datasets (e.
Use when when loading MS/MS spectra from MGF files for FIDDLE model training or evaluation, or when preparing spectrum–annotation pairs for rescore model data augmentation (TCN…
Use when when you need to validate that a development build release workflow (such as dev_build_release.yml for a mass spectrometry data processing project) executes without…
Use when when you have acquired a CCS reference library (such as DTCCSN2 for U13C labeled lipids) and need to verify that it contains the expected lipid classes, CCS values are…
Use when you have received chemical annotations from GNPS spectral library matching and need to (1) assess annotation confidence and validity for downstream analysis, (2)…
Use when when migrating spectral library data from file-based formats (JSON, CSV, binary) into a persistent store and need to support fast filtered queries on metadata and…
Use when you have a high-resolution LC-MS/MS experiment with a measured [M+H]+ or [M-H]− ion mass and optionally a parent ion fragmentation spectrum (peak list with m/z and…
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 during MSP, MGF, JSON, or CSV file parsing when standardizing mass spectra from heterogeneous open mass spectral libraries (OMSLs).
Use when you have constructed or received a SummarizedExperiment object (or similar S4 class) containing MS feature tables, counts matrices, or sample-level metadata, and need to…
Use when after loading an MSP spectral library file into memory using mssearchr's MSP parser, when you need to verify that each spectrum record contains complete and valid…
Use when after training or evaluating a classification model (e.g., MS2DeepScore
Use when when benchmarking or validating the scalability of single-cell algorithms that claim linear or sublinear space complexity, particularly when processing datasets with ≥10…
Use when you have a log2-normalized, zero-mean and unit-variance standardized intensity matrix of metabolite features (rows=metabolites, columns=samples) and need to compute a…
Use when you have executed a complex multi-step processing pipeline (e.g., ENCODE Hi-C uniform processing pipeline) and need to confirm that the generated output files match a…
Use when you have preprocessed, statistically significant LC-MS features (from multiple assays or a single assay) and need to group features that represent the same metabolite in…
Use when you need to enable optional modules in Pyteomics that depend on external libraries not bundled with the core package—such as h5py and hdf5plugin for mzMLb format access,…
Use when after isotopic correction has been performed on MSI ion images and you need to convert normalized intensities into absolute quantitative values.
Use when you have millions of MS/MS spectra in mzML, mzXML, or MGF format that have been converted to low-dimensional vectors via feature hashing, and you need to identify which…
Use when when you have a collection of microbial genomes with predicted BGCs (via antiSMASH), a set of MS/MS spectra (e.g.
Use when you have filtered peak counts from ATAC or DNase-seq data (with GC bias correction and sample/peak filtering applied) and want to annotate peaks by k-mer content rather…
Use when immediately after loading raw MS/MS spectra from .mgf, .msp, or .mzML files, before generating the bag-of-fragments corpus or extracting neutral losses.
Use when you have raw GC-MS output from Agilent Unknowns Analysis (a .CSV with columns Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when after XCMS peak picking and fillPeaks() when you have xcmsEIC and filled xcmsSet objects and need to systematically flag low-quality or unreliable peak integrations prior…
Use when when you need to create synthetic noisy MS/MS spectra for benchmarking or validating denoising algorithms.
Use when after retrieving top-scoring library candidates from a full MS2Deepscore comparison, but before or during final re-ranking.
Use when your metabolomics experiment includes calibration line samples with known concentrations for spiked compounds, and you have computed batch-corrected…
Use when you have a bacterium-phage infection study with normalized peak intensities from FT-ICR MS across multiple phage treatment groups (minimum 2–3 conditions such as HP1,…
Use when you have a GC-MS dataset with Match.Factor scores for each detected compound (output from Agilent Unknowns Analysis or equivalent), and you want to reduce the number of…
Use when when you have raw LC-HRMS metabolomics data in .mzML or .abf format and need to perform untargeted feature detection with chromatographic alignment across multiple…
Use when you have loaded raw mass spectrometry spectral data (in MGF, MSP, mzML, or mzXML format) and need to decide which intensity threshold(s) to use for filtering out noise…
Use when when you have raw LC-HRMS profile-mode data (rt × mz intensity matrices) and need to detect chromatographic peaks using gradient-descent or local-maxima algorithms.
Use when you have aligned features characterized across multiple dimensions (m/z, drift time, retention time) and need to: (1) resolve MS/MS spectra that may contain fragments…
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 a metabolite abundance table (rows=metabolites, columns=samples)
Use when you have raw mass spectrometry outputs (peak areas/heights across samples and fragmentation spectra) that need to be formatted and validated before running the tima…
Use when your input is an AnnData object with expression matrix X as a sparse scipy matrix or Dask-backed array, and you need to apply preprocessing functions (normalization, PCA,…
Use when you have raw Hi-C FASTQ data and need to generate contact maps at kilobase resolution, or you have pre-generated .hic files and need to annotate structural features…
Use when you have a GC-MS dataset with a Match.Factor column (output from Agilent Unknowns Analysis or equivalent) and need to retain only high-confidence compound identifications.
Use when after training contrastive embeddings that unify MS/MS spectra and molecular structures into a shared embedding space.
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 when you need to make OpenMS C++ classes, functions, or data structures callable from Python code, or when verifying that a newly bound C++ component can be imported and…
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 when processing a multi-sample LC-MS metabolomics project after mass-track extraction and retention-time calibration have been applied to all individual samples, and you…
Use when you need to validate that a software project''s release branch is stable and ready for distribution.
Use when after combining multiple EI or MS2 mass spectral libraries and you have access to NIST RI reference files (ri.dat and USER.DBU) and need to assign experimental retention…
Use when when your metabolomic network contains multiple edge types (Biochemical,
Use when after constructing candidate feature pair alignments and retention-time
Use when you have raw tabular experimental metadata (mass spectrometry or NMR sample descriptions, sample-to-treatment mappings, instrument parameters, etc.) that needs to be…
Use when you have experimental peaklist data (CSV or mzML-derived tables) from UHPLC-HRMS/MS instruments (Q-Exactive, Agilent/Bruker/SCIEX Q-TOF) with fragment m/z values and want…
Use when you have m/z values from spatially-resolved mass spectrometry imaging (e.g., MALDI-MSI, DESI-MSI) and need to assign molecular formulae to thousands of features with…
Use when after feature detection and alignment have produced a feature table with MS/MS spectra, and you have access to a reference spectral database (e.g., xenobiotic reaction…
Use when when searching for peptide spectra with unknown or open modifications (i.e., any mass shift within a broad tolerance range rather than a fixed set of known modifications).
Use when you have an unknown compound's mass spectrum (m/z peaks and intensities in . — from HolobiomicsLab/asb-skill-collections
Use when constructing HPLC column feature vectors from raw metadata that includes additive composition flags (e.g., presence/absence or concentration of formic acid, acetic acid,…
Use when you have raw MRM sample files from a LC-MS/MS instrument and need to systematically recover all precursor m/z and product m/z pairs for each transition.
Use when deploying Mass2SMILES on a TensorFlow-CPU build and you need to optimize inference throughput on multi-core systems.
Use when you have computed a histogram of pairwise mass differences from MS imaging data and need to (1) identify which observed mass differences correspond to biologically…
Use when after building a SummarizedExperiment object containing LC-MS peak areas and internal standard assignments, when you need to identify study samples with anomalous…