Use when you have a preprocessed LC-MS feature table (m/z, retention time, intensity columns) and need to identify which features belong together as isotopes or adducts of the…
Use when a Python library exposes functionality that depends on external packages (like sqlalchemy, pandas, or lxml) that are not required for core operations.
Use when when you have a feature abundance table (rows=features, columns=samples)
Use when you have a preprocessed unknown sample spectrum (m/z peaks and intensities) and need to identify the most likely species or reference entries by scoring it again — from…
Use when after performing assignment operations (assign_ri, assign_smiles) or combining multiple library objects (e.
Use when you have a collection of molecular fragments (e.g., from molecular decomposition, retrosynthesis, or synthetic planning) that must be matched to known fragment libraries…
Use when you have extracted MS/MS spectra for a given metabolomic feature across multiple replicates (e.g., after top-TIC filtering) and need to identify which fragments are…
Use when you have uploaded MS/MS data to MassIVE with validated sample-information
Use when when you have a set of query chemicals (e.g., ethyl hexanoate, methyl salicylate, octanal, undecane) and need to evaluate them against reference compound categor — from…
Use when when annotating .msp files with metadata from multiple external web services and you need to monitor which services are slow or unreliable.
Use when you have a GC-MS dataset with a Match.Factor column (or equivalent quality metric) and need to evaluate how many unique compounds are retained at different confidence…
Use when you have a collection of deconvolved mass spectra (in MGF or mzTab format) from GC-MS analysis and need to group them into a molecular network to identify structural…
Use when when you need to understand the computational structure of a modular scientific application (especially one with multiple subprojects or plug-in architectures) and static…
Use when when a Python package is being relocated to a new GitHub organization (e.
Use when you have Nightingale Health 1H-NMR metabolomics assay output (metabolite concentrations in a samples × features matrix) and you want to compute a published metabolic risk…
Use when you have a user-submitted spectrum with associated domain context metadata (e.g., selected as 'microbial origin', 'plant tissue', 'food sample') and need to route that…
Use when when you have aligned ChIP-Seq reads (single-end BED or paired-end BEDPE format) and need to identify enriched genomic regions by comparing ChIP signal against control…
Use when after normalization of a metabolomic feature matrix but before statistical testing, when you have both QC (technical replicate) and non-QC (study) samples and need to…
Use when when preparing augmented variants of ion images (single-channel 2D arrays or multi-channel spectral images) for contrastive learning in mass spectrometry imaging tasks.
Use when when raw spectral data exists in one mass spectrometry file format but downstream analysis requires a different format; when integrating spectra from multiple sources or…
Use when you have Spectra objects in an R environment and need to apply Python MS algorithms (e.g., matchms similarity scoring, spectrum normalization, or filtering) that operate…
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 input GC-MS data (netCDF or mzML format) exhibits overlapping chromatographic peaks where multiple analytes co-elute at the same retention time, resulting in composite…
Use when you have a preprocessed GC-MS dataset (from spreadOut) with standardized column names (Compound.Name, Component.RT, Base.Peak.MZ, Component.Area, Match.Factor) and a…
Use when you need to create a synthetic feature table with known, ground-truth condition effects for method validation when: (1) testing normalization or batch-correction…
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 you have a baseline GNN model trained on a molecular property prediction task (e.
Use when you have multiple CSV feature tables from independent metabolomic experiments, each with RT and m/z annotations, and you need to produce a single consolidated feature…
Use when when tabulating chemical annotation enrichment (e.g., GNPS spectral library matches) across sample groups stratified by metadata category (e.g., sample type, extraction…
Use when you have unaligned MS2 spectra from one or more samples (in formats like .mgf, .mzML, or .mzXML) and need to compare them in a retention-time-agnostic manner.
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 when you have transcript-level quantification files (e.g., Salmon quant.sf.gz, kallisto abundance.h5, or RSEM .results) and need to construct a gene-level count matrix…
Use when after computing expected adduct ions for a metabolite using a derivatizing matrix ruleset, validate the predicted m/z values and adduct formulas against a curated…
Use when after applying biotransformation rules to generate candidate product structures from input molecules, when the same transformed structure can be produced via multiple…
Use when after running a ViMMS Environment simulation with save_eval flag enabled, when you need to preserve the link between each simulated MS/MS scan in the output mzML file and…
Use when you have a sparse chromatin accessibility matrix (ATAC-seq or DNAse-seq counts per peak per sample), matched peak-annotation assignments (e.
Use when you have mass spectrometry data stored in a non-standard format (SQLite database, custom indexed gzip files, or other database backends) and want to enable pymzML's…
Use when you have spectrum or chromatogram data stored as XML strings (e.g., in a SQLite database indexed by spectrum ID) and need to access individual spectra by ID or iterate…
Use when when you have raw or centroid-mode LC-MS All-ion fragmentation (AIF) spectra and need to generate or match against ion fragment databases.
Use when when you have processed LC-MS/MS spectral data in .mgf format with feature identifiers and need to compute a pairwise similarity matrix to support interactive exploration.
Use when when you have vendor mass spectrometry raw files (e.g., .raw format) that must be converted to an open format (Aird) using a Windows .
Use when when a user has prepared a custom collection of metabolite sets (e.g., from spectral fragmentation clustering, literature curation, or domain-specific grouping) in CSV or…
Use when after running RAMClustR clustering on XCMS-processed metabolomics data, export spectral data when you need to share clustered spectra with external annotation software…
Use when you have a compiled EI or MS2 library object (from read_lib or c() combination of multiple sources) and a local NIST library installation with accessible ri.dat and…
Use when you need to persist and communicate the health status of multiple external web services queried during an annotation run.
Use when you have mass spectrometry data (m/z, retention time, intensity) loaded into a Pandas DataFrame and need to explore the full 3D structure of a peak map interactively,…
Use when when you have annotated representative LCMS samples (raw mzML files + labeled feature tables in mzmine CSV format) and need to convert them into balanced or unbalanced…
Use when when extending MSMetaEnhancer with a new local chemical transformation (e.g., SMILES to InChI) that should execute non-blockingly within an asynchronous annotation…
Use when when preparing to run ORA on a metabolomics study: you have a list of detected metabolites from your experiment and need to determine which metabolites from the full…
Use when after applying AbundanceSimilarityParam (with threshold ≥0.7 and log2 transform) to retention-time-based feature groups from SimilarRtimeParam, when you need to examine…
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 when converting MS/MS spectra into spectral documents for Spec2Vec embedding, and you want to capture chemical relationships implicit in the fragmentation pattern (e.g.,…
Use when you have a normalized single-cell expression matrix (e.g., after SCTransform) and need to compute gene-level covariance structure for pathway enrichment analysis (e.g.,…
Use when after GNPS spectral library matching has been completed on a batch of MS2 spectra from public MassIVE datasets and you need to aggregate chemical annotations into a…
Use when when preparing SMILES strings as training targets for a sequence-to-sequence
Use when you have computed multiple independent scoring functions (e.g., standardised strain correlation and IOKR) for a large set of potential genomic–metabolomic links and wish…
Use when when setting up a DESeqDataSet from count matrices or transcript quantification, you must specify a design formula before running DESeq() if your experiment has batch…
Use when you have variable-length MS/MS peak lists (m/z arrays and intensity arrays) that must be fed into a transformer architecture for tasks like compound identification or…
Use when before peak detection on a composite or individual mass track when you need to filter out low-intensity noise and baseline drift without removing true signal.
Use when you have loaded a feature-by-pixel intensity matrix from an MSI HDF5 container and need to perform dimension-preserving corrections (e.