Use when when working with spatial transcriptomics datasets (e.g., Slide-seq v2, MERFISH) stored in AnnData format and you need to identify genes whose expression shows…
Use when when you need to understand how a multi-instrument mass spectrometry platform (such as mzmine) selectively routes data to different processing pipelines based on — from…
Use when you have MS-DIAL lipid identifications from an Orbitrap or TOF mass spectrometer and need to remove spurious or low-confidence assignments before downstream metabolomics…
Use when you have raw or processed FT-ICR MS spectra with detected peaks (m/z values) and need to: (1) assign elemental compositions to each peak, (2) filter assignments by mass…
Use when you are receiving molecular structures from external sources (COCONUT database, ZINC database, user-provided chemical data) in varying formats (SMILES strings, InChI…
Use when you have preprocessed mass spectrometry fragmentation data (neutral losses and fragment masses extracted and noise-filtered) and want to discover hidden structural motifs…
Use when when you need to generate synthetic LC-MS/MS data to test fragmentation
Use when when processing collections of in-silico mass spectra from OMSLs (Open Mass Spectra Libraries) where the adduct field is absent, null, or not explicitly specified in the…
Use when when you have Spectra objects in R and need to apply Python MS library functionality (spectral similarity scoring, filtering, normalization) without leaving the R…
Use when you have raw GC-MS output files (vendor formats or netCDF) from a chromatography instrument and need to prepare them for automated peak deconvolution and spectral…
Use when when you have loaded a chemical database (e.g., HMDB pickle file) and need to understand how many distinct molecular formulas remain after filtering for a specific m/z…
Use when you have MSBERT-preprocessed spectral datasets (GNPS, MoNA, or MTBLS1572 format) with SMILES annotations before training a spectral embedding or compound identification…
Use when after executing an end-to-end structure annotation pipeline (such as BAM) on a validation dataset with known reference annotations.
Use when you have a pretrained TCN spectrum encoder from formula prediction and need to train a rescoring model that ranks formula candidates by confidence.
Use when you have an experimental MS/MS spectrum (m/z and intensity pairs with known precursor m/z) and need to identify the compound by searching against public repositories or a…
Use when your task requires a pretrained convolutional encoder (ResNet18) to produce fixed-size representation vectors of a specific dimensionality (e.g., 512 dimensions) rather…
Use when you are preparing to run LipoCLEAN on MS-DIAL output and need to create or update a configuration file, or you have switched between MS-DIAL 4 and MS-DIAL 5 data and need…
Use when before executing a bioinformatics pipeline that depends on multiple R packages with strict version constraints (e.g., DaDIA, which requires R ≥4.0, XCMS ≥3.11.4, and…
Use when before submitting peak data or other inputs to a machine learning classification API for the first time, after a model update, or if you encounter unexpected prediction…
Use when after completing feature annotation with the annotateRC function on LC–MS All-ion fragmentation (AIF) datasets, when you need to persist ranked metabolite candidates,…
Use when when implementing a new ComputeConverter subclass for MSMetaEnhancer that performs local chemical structure conversions using RDKit (e.g., SMILES to InChI, canonical…
Use when you have an mzPeak file (uncompressed ZIP archive containing Parquet files) and need to extract and work with spectrum metadata (scan descriptions, precursors, selected…
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 apply batch normalization after dense hidden layers (but not the final embedding layer) in a deep neural network trained on MS/MS spectral data, particularly when the…
Use when when you have a binned Hi-C cooler file, an associated eigenvector track (from prior eigs_cis calculation), and need to measure how strongly the genome is partitioned…
Use when when you have completed a PALS pathway analysis on a clean metabolomics peak intensity matrix and pathway annotation set, and you need to verify that the ranked pathway…
Use when you have a cooler Hi-C contact matrix file and an associated eigenvector track (from prior eigs_cis calculation or similar), and you need to quantify the preferential…
Use when after generating simulated mzML output from ViMMS and you need to compare it against real acquisition data.
Use when you have collected or inherited sample-information metadata from multiple sources (e.
Use when when deploying an R package from a non-CRAN repository (e.g., r-universe, Bioconductor, GitHub), or when verifying that a package build is reproducible and meets CRAN…
Use when immediately after peak detection and feature table generation from LC-MS data, when you need to rank or filter features by confidence before annotation or statistical…
Use when use STOCSY when you have preprocessed 1H NMR spectral data with an unidentified peak of interest (driver signal at a specific δ ppm value) and need to determine its…
Use when you have LC-IM-MS/MS experimental data (raw mzML or vendor format) containing signals from N-Me derived unsaturated sterol lipids and need to assign double-bond positions…
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 loaded a Bruker Solarix transient file (.d format with .ser or .fid content) and need to generate a processed mass spectrum for peak picking and molecular…
Use when when converting mzML files to imzML format and the source mzML contains multiple scan filters (e.g., different MS/MS isolation windows, ionization modes, or mass ranges…
Use when after completing peak calling and cell annotation in an ArchR project, when you intend to perform trajectory analysis using STREAM rather than ArchR's native monocle3 or…
Use when after RAMClustR clustering and molecular weight inference via do.findmain, when you need to export deconvoluted cluster spectra for import into external annotation tools…
Use when when building a multi-backend visualization library where users specify both a plot type (spectrum, chromatogram, peakmap) and a backend (matplotlib for static output,…
Use when after running the ENCODE Hi-C uniform processing pipeline or Juicer on FASTQ input data and generating a .hic output file.
Use when you have generated or obtained a two-dimensional mass-spectrometry intensity matrix (m/z × retention time scan points) with simulated or experimental peak shapes, noise,…
Use when you have peak-picked features with m/z, drift_time, retention_time, and intensity columns, and you need to identify monoisotopic peaks and their charge-state-specific…
Use when after NMR or MS data acquisition and preprocessing (phasing, baseline correction) when you have a SummarizedExperiment object containing assay intensity matrix with QC…
Use when after peak detection on individual GC-IMS samples, when you need to assign consistent cluster IDs to peaks detected across multiple samples to enable cross-sample…
Use when a GitHub repository displays a CI workflow badge (e.g., passing/failing status in README) and you need to verify that the reported status is accurate, reproduce the CI…
Use when you have raw chromatography–mass spectrometry data (GC-MS or LC-MS) in 2D m/z–retention time format and need to identify and discriminate multiple analytes while avoiding…
Use when you have OnDiskMSnExp CE-MS objects with known marker compounds (e.g., Paracetamol EOF marker) and need to extract their migration time positions to establish a…
Use when when you have CE-MS raw data (mzML or netCDF format) with extracted ion traces for target compounds and need to identify peak boundaries and extract quantitative peak…
Use when you have generated predicted fragment spectra for a set of compounds using CFM-ID or similar in-silico prediction tools and need to organize these results into a…
Use when after applying one or more intensity drift correction strategies (Internal Standard correction, statistical drift correction, custom or weighted bracketing) within…
Use when when you have aligned ATAC-seq BAM files and need to quantify Tn5 transposase insertion patterns around specific genomic coordinates (motif sites, peaks, regulatory…
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 you have 1D or 2D NMR spectra (1H and/or 13C) and need to predict unknown molecular structure (formula and connectivity) up to ~19 heavy atoms; or you have a set of…
Use when after batch effect removal and data integration, when you have a feature-by-sample matrix (finalData) and wish to separate and visualize sample groups by their…
Use when you have executed multiple NPDtools database search pipelines (Dereplicator, VarQuest, Dereplicator+, or MetaMiner in different modes) on identical test spectra or RiPP…
Use when when processing LC-MS data with multiple overlapping m/z scan windows and observing sawtooth-pattern distortions in EICs during tardisPeaks() execution.
Use when after merging methylation call files across all samples into a unified methylBase object (via unite()), when you need to assess whether biological replicates cluster…
Use when you have mass spectrometry data loaded into a pandas DataFrame with m/z, retention time, and intensity columns, and need to confirm that pyOpenMS-Viz can produce…
Use when you have multiple MSP or spectral library files (e.g., one per batch of analytical standards, or organized in a directory structure) that need to be read and merged into…
Use when you have raw IMC and SIMS image data from the same tissue region(s) and need to: (1) register the two modalities spatially, (2) segment individual cells across both…