Use when when you have ensemble predictions (e.g., from Monte-Carlo Dropout inference with N ≥ 10 forward passes per input) and need to distinguish high-confidence from uncertain…
Use when you have a curated dataset of molecular structures (or molecular descriptors) paired with experimentally measured or reference collision cross section values, and you…
Use when you have log2-transformed, standardized peak intensity matrices with metabolite annotations (peak ID → KEGG/ChEBI IDs) and need to test whether groups of peaks co-vary…
Use when when you have processed LC-MS/MS data with precursor m/z, ionization mode, collision energy (if available), and fragment peak lists (m/z and intensity pairs), and need to…
Use when after rewriting or refactoring a Python module (such as calculate_feature_overlap.py
Use when after cluster-based filtering has produced a set of candidate KEGG compounds for each feature cluster in untargeted LC-MS data, and you need to rank these candidates by…
Use when you have a set of lipid targets defined by species name, acyl chain composition, and expected adducts, and you need to configure a targeted mass spectrometry workflow…
Use when you have a detected LC-MS feature table (with m/z, retention time, and intensity columns) and need to identify which features are derivatives of the same parent molecule…
Use when you have a GNPS molecular network (in GML or GraphML format) and a completed MS2LDA experiment on ms2lda.org, and you want to annotate network nodes with detected…
Use when you have a trained regression model (e.g., a neural network or similar predictor) and a held-out test set with ground-truth continuous labels, and you need to measure…
Use when when you have installed or updated a DNA methylation analysis tool (e.g., ChAMP) and need to verify that it produces documented expected outputs on a reference simulation…
Use when you have selected a subset of public tandem MS files from ReDU/MassIVE that have been processed through GNPS spectral library matching, and you need to organize their…
Use when when preparing a chemical database for virtual or real MS/MS acquisition, and you need to focus on a specific m/z window (e.g., 100–1000) that matches your instrument's…
Use when you have MS2 spectral data (precursor m/z, retention time, and fragment ion patterns) from UPLC-HRMS analysis of environmental or biological samples and need to assign…
Use when you have raw RNA-seq count data (from HTSeq, featureCounts, Salmon, or similar quantification tools) organized in a count matrix with samples as columns and genes as…
Use when raw NetCDF-format GCxGC-MS chromatograms exhibit steady or increasing baseline intensity caused by instrumental contamination, column bleeding, or thermal drift;
Use when when comparing two MS/MS spectra using modified cosine similarity and the precursor m/z values differ, indicating potential neutral losses, adduct variations, or analogs…
Use when you have generated or received a mass spectrometry data file in a structured format (e.g., mzPeak, Parquet-based archive) and need to verify it conforms to the published…
Use when after importing raw metabolomics data (e.g., from Metabolon, Nightingale, SomaLogic, or Olink platforms) into a Metaboprep object, but before quality control or…
Use when training a deeply regularized deep neural network on a large molecular feature dataset (e.
Use when you have split multi-assay LC-MS intensity data into training (90%) and test (10%) subsets with assay-specific column prefixes, and you need to fit a discriminant or…
Use when when analyzing spatial molecular data (e.g., from tissue sections or microscopy) where you need to build k-nearest neighbor graphs on high-dimensional coordinate arrays…
Use when when you have scored GCF-MF (gene cluster family–molecular family) links using two or more complementary scoring approaches (e.g., standardised strain correlation and…
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 assembled genome FASTA sequences (from SPAdes, metaSPAdes, or antiSMASH output) and need to systematically identify precursor peptides corresponding to a target…
Use when when you have ionized adduct structures (SMILES or MOL format) from a prior ionization-state determination step and need to create multiple low-energy 3D conformations…
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 you have run the same mass spectrum through molecular formula assignment under different parameter settings (e.
Use when you have a table of detected chromatographic peaks (e.g., from CentWave peak detection in xcms) and need to isolate a single target m/z (e.g., m/z 304.1131 for a…
Use when you have CE-MS raw data (mzML or netCDF format) containing a target compound of known m/z ratio and you need to resolve it as a distinct peak on the effective mobility…
Use when processing raw MS/MS spectra (in MGF, mzML, mzXML, JSON, or MSP format) prior to MS2Query library matching or MS2Deepscore embedding calculation.
Use when when ingesting mass spectral libraries (EI or MS2) where SMILES information is embedded in the Comment field rather than in a dedicated SMILES metadata field—particularly…
Use when after auditing and optionally rescaling a mass track (composite mass chromatogram) when you need to subtract background signal and set dynamic prominence thresholds for…
Use when when you have a GNPS molecular network (classical or feature-based) and corresponding MS2LDA experiment results, and you want to annotate network nodes with discovered…
Use when you are preparing to perform effective mobility transformation of CE-MS data and must establish the electrophoretic system's calibration context.
Use when you have MS/MS spectra with fragment frequency annotations (from consensus spectrum generation) and need to decide which fragments to retain versus remove.
Use when you have identified a claim that one tool outperforms another (e.g., 'IDSL.IPA outperforms MZmine 2 and xcms') in a research article's abstract or introduction, but the…
Use when you have raw or partially processed metabolomics data (mzML/mzXML format) from LC-MS or GC-MS runs and need to apply standardized feature detection, alignment, and…
Use when you have CpG methylation call files (from Bismark or MethylDackel) and need to load them into R for differential methylation analysis, but anticipate memory constraints…
Use when you have generated a GNPS mass spectral molecular network (in classical or feature-based mode) and want to annotate network nodes with substructural motifs from MS2LDA or…
Use when you have a raw GCxGC-MS chromatogram in NetCDF format (.cdf file) and need to import it into R as a 2D-TIC object for preprocessing (smoothing, baseline correction, peak…
Use when building or maintaining a system that fetches metadata from multiple independent external web services and needs to diagnose why annotation runs fail or slow down.
Use when when comparing GNPS chemical annotations across two or more groups of samples (defined by ReDU sample-information categories such as sample type, extraction method, or…
Use when you have transcript abundance files (e.g., Salmon quant.sf.gz, kallisto abundance.h5, RSEM .isoforms.results) from a quantification tool and need to construct a…
Use when you have computed k-nearest neighbors for spatial coordinates (e.g., via pynndescent or another NN backend) and need to store the resulting adjacency and distance…
Use when when you have mass-to-charge (m/z) values from mass spectrometry imaging or other MS experiments and need to assign molecular formulae with high precision, especially in…
Use when when you need to verify whether a specific mass spectrometry instrument platform (vendor and model), acquisition mode (e.g., targeted, ddMS2-topN, AIF, direct infusion,…
Use when when you have raw LC-MS all-ion fragmentation (AIF) chromatograms in centroid mode and need to prepare them for metabolite annotation using fragment ion matching.
Use when you have a validated or curated dataset (e.g., a TSV or gzip-compressed
Use when after training a NeatMS neural network model on labelled peak data (High_quality, Low_quality, Noise) and you need to determine the optimal probability threshold for…
Use when you have IM-MS lipidomics data acquired on samples spiked with fully labeled U13C lipid standards (e.g., U13C yeast extract), and you need to assess whether systematic…
Use when you have a connected subnetwork of feature ions that have been validated as belonging to the same empirical compound (khipu instance), with isotope and adduct edges…
Use when when analyzing imaging mass spectrometry datasets where you need to reduce high-dimensional peak intensity features while preserving spatial structure, and when automatic…
Use when you have LC–MS/MS data processed through MZmine2 or MZmine3 and need to construct a feature quantification table for natural product discovery pipelines (e.g., INVENTA…
Use when after generating a peak table from XCMS peakTable() output in an untargeted LC-MS metabolomics workflow, if your experimental design includes quality control (QC) samples…
Use when you have extracted clustering or classification accuracy metrics (NMI, ARI, purity scores) for two or more competing methods evaluated on multiple datasets, and need to…
Use when you have TSV or CSV files containing structure-organism pairs (with columns for structure identifier and organism identifier) and need to count unique pairs, unique…
Use when you have an isotope-corrected or raw MSI dataset stored in HDF5 format following Cardinal::HDF5 conventions, a user-provided internal standard definition (sample…
Use when when you have detected peaks in a direct injection FTICR-MS mzML file (or similar high-resolution MS format) and need to assess whether m/z measurements are accurate and…
Use when after extending ChIP sample reads to their predicted fragment length and constructing local lambda bias tracks (incorporating d-scaled, 1 kb, 10 kb, and genome-wide…