Use when you have computed frequent fragmentation patterns from a collection of MS/MS spectra using mineMS2, and you want to focus pattern interpretation on subsets of spectra…
Use when you have cloned or loaded a deep-learning architecture extension (e.g., chemprop-IR) and need to verify that its feature extraction component can be instantiated and…
Use when you have executed an end-to-end SnapATAC2 pipeline on the pbmc10k_multiome dataset (or a similar single-cell ATAC-seq dataset with a published reference) and need to…
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 processing raw IM-MS data (Agilent MassHunter .d or UIMF format) that contains jagged, low-abundance ion peaks or when saturation repair has been applied and the…
Use when when training a regularized deep neural network for molecular property regression (e.g., retention time prediction on the METLIN SMRT dataset with 80,038+ samples), use…
Use when you need to serialize heterogeneous data (e.g., index integers and file offsets of different byte widths) into a compact binary format, or parse a binary file format…
Use when your gene expression matrix or pathway collection uses identifier formats incompatible with your enrichment analysis tool (e.g., gene symbols vs.
Use when you have paired-end ChIP-Seq data (BEDPE format) and need to determine the empirical fragment length (insertion length) before peak calling.
Use when you have raw LC-MS/MS data in mzML or mzXML format and need to: (1) identify the top-abundance MS1 signals in an LC run, (2) compute a single scalar metric (separation…
Use when you have raw MS2 spectra (m/z and intensity pairs) that you want to match against a large training dataset of annotated library spectra (e.g., GNPS), and you need to…
Use when you have a feature table from untargeted LC-MS (m/z, retention time, intensity) and need to annotate which observed m/z values correspond to isotopologues and adducts of…
Use when you have a user-defined reference list of isolated, high-confidence chromatographic peaks (ground-truth) matched across multiple LC-HRMS samples, and you need to produce…
Use when when you have pre-computed embeddings for query and reference MS/MS spectra, computed their cosine similarity matrix, and need to measure retrieval success by verifying…
Use when when setting up a bioinformatics pipeline (such as HiC-Pro) that depends on multiple compiled or independently distributed binaries and you need to confirm that all…
Use when a user supplies a custom feature list from external feature-finding software (vendor tools, alternative open-source pipelines) instead of using pyOpenMS automatic…
Use when you have raw MS/MS spectra (in formats like mzML, json, mgf, msp, mzxml) that contain background noise or numerous low-intensity peaks before running MS2Query library…
Use when you have two peak-picked, conventionally aligned untargeted LC-MS metabolomics datasets (metabData objects) acquired under different conditions and need to ident — from…
Use when when you have access to annotated MS/MS spectra from a specific ionization mode (e.g., negative ESI) or adduct class (e.
Use when you have aligned ATAC-seq BAM files from Tn5-based chromatin accessibility assays and need to perform footprinting analysis.
Use when you have at least 3 raw mass spectrometry samples in open formats (mzML, mzXML, CDF) from untargeted metabolomics experiments and need to configure parameters for XCMS,…
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 you have a .msp spectral library file with sparse or incomplete metadata (e.
Use when after LDA modeling has inferred a set of Mass2Motifs (in JSON format) from preprocessed MS/MS spectra and you need to annotate these motifs by retrieving matching entries…
Use when you have a Cardinal MSImagingExperiment object (e.g., from imzML or Analyze 7.5 files) and need to retrieve the complete set of m/z values and their intensities for…
Use when apply this filter after loading raw .idat files or beta-valued matrices from HumanMethylation450 or EPIC methylation arrays when you need to remove probes with…
Use when you have received raw FT-ICR transient data from Bruker Solarix or ThermoFisher instruments and need to perform signal processing, apodization, calibration, or molecular…
Use when when you need to create negative control or background-only reference datasets for LC/GC-MS analysis pipelines—specifically to validate peak-picking algorithms, assess…
Use when you have acquired full-scan mass spectrometry imaging data (e.g., from a mouse bladder or tissue section) with detected m/z features and want to assign chemical…
Use when when you have MS/MS spectra from both query compounds and a reference library and need to decide which similarity metric will maximize identification accuracy (true…
Use when after rewriting or modifying a Python module (such as calculate_feature_overlap.py
Use when when you have loaded aligned peak-alignment data from a molecular networking task and need to distinguish high-confidence, reproducible peak alignments from noise or…
Use when after peak picking across individual spectra in an MSImagingExperiment,
Use when you have an unknown electron ionization (EI) mass spectrum and need to identify the compound by comparing it against a reference library (msp file format).
Use when processing feature lists from LC- or GC-HRMS data (in mzML format or as custom feature tables with m/z and molecular formula columns) and you need to flag potential PFAS…
Use when when building a comprehensive reference spectral library for metabolomics or chemical identification, you have multiple source libraries in different formats (msp, mgf,…
Use when you need to transfer retention time predictions from one chromatographic method to another, but have access to only a small number (≥10) of molecules with known retention…
Use when apply TIC normalization when you have raw, unprocessed mass spectrometry data (Cardinal objects or imaging matrices with 10,000+ m/z features and 1,000+ spectra) where…
Use when when you have trained a predictive model (e.g., neural network or regression model) that outputs continuous scores (such as Spearman correlation coefficients) for…
Use when after chromatographic peak detection on preprocessed LC-MS data, when you have detected features (peaks) in multiple samples and need to establish which peaks ac — from…
Use when designing multi-batch LC/GC-MS experiments where you need to control for batch effects (e.g., instrument drift, reagent lot variation) and have identified both a balance…
Use when after installing a package in development mode (e.g., via `pip install -e .[dev]`) to verify the package functions as intended, or before submitting pull requests to…
Use when after MS2 fingerprints have been generated by counting MS2 peaks and neutral losses in each sample, and you have aligned them into a MemoMatrix (sample-by-fingerprint…
Use when after generating a corpus/features JSON file from raw MS2 fragmentation
Use when you have spatial metabolomics data with semicolon-delimited isomer name annotations (such as the 'all_IsomerNames' column in SpaMTP Seurat objects) and you need to reduce…
Use when you have SWATH-MS raw data (mzML or vendor format) from an untargeted metabolomics experiment and need to identify metabolites.
Use when you have two or more mass spectral libraries in different formats (NIST binary exports converted to MSP, MoNA downloads, RIKEN public databases, GNPS MGF, or batches of…
Use when when evaluating whether a mass spectrometry analysis platform (such as mzmine) has comprehensive module support across multiple ionisation and separation techniques (LC,…
Use when when you need to validate that a Python package (or update to it) is accessible to end users through official distribution channels, or when you are preparing a release…
Use when when converting raw metabolomics data (tab-delimited text files, Sciex OS exports) into a structured object for batch processing, or when you need to organize…
Use when when building an automated converter discovery and job enumeration system where converter classes are dynamically loaded from package directories and you need to extract…
Use when when xcms has produced misaligned feature groups and you need to extract raw LC-MS profiles from source files into a structured format acceptable by ncGTW's realignment…
Use when when you need to confirm that a Java project's GitHub Actions workflow (e.g., 'dev_build_release.yml') has completed successfully and generated usable build artifacts;
Use when when you have a partially documented or undocumented MS analysis pipeline and need to verify its correctness, trace data provenance through multiple processing stages,…
Use when before running HiC-Pro's normalization stage on aligned Hi-C BAM files. Specifically, when you have SAM/BAM-formatted aligned Hi-C reads that need bias correction and…
Use when you need to verify whether a GitHub Actions workflow badge (e.g., main.yml) accurately reports the CI pipeline's true pass/fail status.
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 after XCMS feature detection and retention time correction, when you need to group features derived from the same compound.
Use when you have a normalized LC-MS/MS metabolite abundance matrix (e.g., from MS-DIAL preprocessing) with multiple samples across experimental groups (e.
Use when when you need to understand how a complex feature or architectural pattern was implemented in a codebase, particularly when the current README or documentation does not…