Use when when building reproducible Python-based computational workflows that must serve both beginner and expert users; when the analysis requires interactive parameter tuning,…
Use when after MamsiStructSearch has completed structural clustering of statistically significant LC-MS features (p < 0.
Use when after computing deviations for both motif and kmer annotations on the same chromVAR dataset, when you need to determine whether kmers and motifs are redundant predictors…
Use when you have raw MS/MS spectra (in MGF or mzML format) with unscaled peak intensities and noise artifacts, and you plan to rank chemical formulas, predict adducts, or score…
Use when you have an MS/MS peak list and need to remove electronic noise—specifically
Use when when you have SMILES strings representing neutral organic molecules and need to enumerate the likely protonated (e.g., [M+H]+) and deprotonated (e.
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 when performing targeted peak detection on LC-MS data where compounds have been assigned expected ionization polarities (positive or negative mode) in the target list,…
Use when after RDKit generates multiple 3D conformers from ionized molecular structures using distance-geometry embedding, before filtering with ASE-ANI or submitting to quantum…
Use when you have an observed m/z value from mass spectrometry imaging and need to assign a chemical formula with high confidence.
Use when you have raw .idat files or a beta-valued matrix from an Illumina HumanMethylation450 or EPIC array experiment and need to import the full probe set into R for downstream…
Use when after defining a transformer encoder architecture with multi-head self-attention and positional encoding, and before training or inference on mass spectrometry data.
Use when you need to verify that a GitHub Actions workflow (such as 'dev_build_release.
Use when you have a large gene expression matrix (e.g., thousands of genes) from normalized microarray or RNA-seq data and need to reduce computational burden before running…
Use when when you have mass spectral libraries from multiple sources (NIST, MoNA, RIKEN, GNPS) in disparate formats (MSP, MGF, MOL folder structures) or with misaligned metadata…
Use when you have raw GC-MS data (in netCDF or vendor format) containing overlapping chromatographic peaks from complex mixtures where individual compound spectra cannot be…
Use when you have executed a spectrum search against one or more domain-specific
Use when you have a collection of records in a standardized format (e.g., MassBank plain-text or structured records) that must be validated before commit or publication.
Use when you have raw LC–MS data in vendor-proprietary or uncorrected formats (e.g., .raw, .d) and need to perform targeted peak detection, retention-time correction, or automated…
Use when after GNPS spectral library search has returned matched chemical annotations (with m/z values and cosine similarity scores) for MS/MS spectra.
Use when after constructing individual mass tracks from mzTree data bins and before alignment across samples.
Use when after identifying differentially methylated bases or regions (via calculateDiffMeth() and getMethylDiff()), when you need to characterize WHERE these methylation changes…
Use when you have a genome annotation GTF file and need to identify all transcript-level alternative splicing events (exon skipping, intron retention, alternative splice sites,…
Use when you have observed mapping rate or quantification disagreement (e.g., >0.1% divergence in mapping rate or Pearson r < 0.
Use when analyzing MALDI-mass spectrometry imaging data in which sodium or other alkali metal contamination is suspected, or when peak lists show unexplained mass differences in…
Use when you have an experimental MS/MS spectrum (e.g., from MassBank or local data) and need to identify significant fragment ions above noise, assign occurrence scores to peaks,…
Use when you have fingerprint or spectrum data that requires compound-class annotation but prefer not to run SIRIUS locally, or need to integrate predictions into an automated…
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 mass tracks have been aligned across samples into a MassGrid structure and retention time calibration dictionaries (rt_cal_dict) have been computed for eac — from…
Use when you have two or more independent, standardised scoring functions that rank the same set of candidate pairs (e.
Use when analyzing RNA-seq count data from a DESeq2 workflow where you have fitted negative binomial generalized linear models and need to extract final results.
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 raw Agilent MassHunter (.d) or UIMF mass spectrometry files exhibit jagged or noisy peaks, particularly for low-abundance ions where signal-to-noise ratio is poor.
Use when when training Word2Vec embeddings on mass spectra represented as peak-word documents, and you need to preserve the quantitative intensity relationships between fragments…
Use when when you have 1H-NMR metabolite measurements from Nightingale Health assayed on a new cohort and wish to compute risk scores (e.g., all-cause mortality, cardiovascular…
Use when after sending HTTP requests to API endpoints (such as /classify or /model/metadata on an NP-Classifier server) to verify that the response is parseable JSON and contains…
Use when you have integrated, normalized lipidomic and metabolomic feature tables from the Multi-ABLE method or similar concurrent multiomics workflows, with matched sample…
Use when you have raw mass spectrometry spectra (in MGF, mzML, or similar formats) that must undergo standardized preprocessing before library matching, similarity searching, or…
Use when you have draft metabolic reconstructions in SBML or standard format for multiple organisms in a microbial community (e.
Use when you have completed cluster-based filtering of KEGG candidate assignments in untargeted LC-MS metabolomics and need to rank those candidates by biological plausibility…
Use when you have a GNPS mass spectral molecular network and wish to annotate its nodes with both chemical class assignments (from GNPS public library matches) and MS2LDA-derived…
Use when you have a feature table from LC- or GC-HRMS data (either detected via pyOpenMS or imported as a custom feature list) containing m/z, retention time, and intensity…
Use when after constructing a background set for ORA in metabolomics: you have loaded an experimental detection list and a metabolomics pathway database, applied background-set…
Use when when preparing XCMS peak tables for quality classification and you observe that the default RSD threshold (0.3 or 30%) is either too permissive (retaining noisy EICs) or…
Use when you have downloaded LC-MS spectral peak data (DOI 10.25345/C5FD2F or equivalent) and need to build a supervised deep neural network classifier to distinguish peak classes…
Use when when you need to verify the current operational status of a software project across multiple dimensions (CI/CD, code quality, test coverage, containerization, archival)…
Use when when processing raw or centroid mass spectra (e.g., ESI-MS or FT-ICR data from Bruker .d or Thermo .raw formats) and you need to remove instrument noise and low-abundance…
Use when you have validated intermediate JSON data (conforming to the Experiment Description Specification) and need to configure how it should be converted to a supported output…
Use when you have a negative-mode or positive-mode LC-MS feature table with observed m/z values and peak intensities, and you need to identify which metabolites (by KEGG ID) are…
Use when you have multiple replicate MS/MS spectra for the same metabolic feature (e.g., 66 top-TIC spectra for feature 1982) and need to identify robust peaks by merging nearby…
Use when processing spectral datasets from open mass spectra libraries (OMSLs) where structural identifiers and ionization metadata are incomplete or inconsistent.
Use when when you need to simulate LC-MS/MS data for fragmentation strategy development and do not have (or wish to augment) real experimental chromatograms.
Use when when you have salmon quant.sf.gz output files from pseudoalignment-based transcript quantification and need to convert transcript-level abundance estimates and counts…
Use when you have a trained GNN model (stored as .h5 weights) and molecular graph representations (SMILES strings and/or 3D coordinates), and you need to compute predicted CCS…
Use when after extracting raw MS/MS spectra from mzML files but before consensus spectrum generation, when you observe high-resolution fragment lists where nearby peaks (within a…
Use when you have loaded a feature-by-pixel intensity matrix from an MSI HDF5 container and need to perform dimension-preserving corrections (e.
Use when when comparing quantification results between two versions of a tool (e.g., salmon 2.0 Rust rewrite vs.
Use when when deploying containerized versions of a multi-variant application (e.g., CLI, development, Linux, and Windows flavors) and you need to verify that each built image…
Use when you have a MemoMatrix (sample-by-fingerprint matrix) from aligned MS2 spectra and need to visually compare sample similarity or clustering patterns, especially when…
Use when you have completed the MS2LDA LDA modeling phase and possess motifset.json or motifset_optimized.json files containing inferred Mass2Motifs.