Use when you have a query mass spectrum matched to multiple candidate metabolites (by accurate mass, database lookup, or spectral similarity), and you possess or can train a DNN…
Use when you have intracellular metabolomics abundance data (absolute or relative concentrations) for multiple cell lines or conditions, a constraint-based stoichiometric…
Use when when you have a list of known metabolite concentrations and their corresponding J-coupling constants (spin systems) and need to generate realistic 1D 1H NMR spectra or 2D…
Use when you have a raw metabolite count data frame (e.g., c57_nos2KO_mouse_countDF)
Use when you have raw or baseline-corrected metabolite abundance measurements from mass spectrometry and need to prepare them for batch effect correction (e.g., CordBat) or…
Use when after generating or filtering transformation products using generateTPs() or filter(), when you need to annotate MS/MS spectra using MetFrag and require a database of…
Use when you have raw NMR metabolomics measurements paired with pre-analytical metadata (e.g., processing delay times, sample type designations [plasma vs.
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 you have ion-mobility mass spectrometry metabolomics data with putative metabolite identifications (e.g., from database matching) and want to reduce false positives by…
Use when when you have access to the MAGMa source code and need to understand or audit how in silico metabolite candidates are enumerated from parent structures.
Use when you have extended a metabolite identification tool (such as Met-ID) to support a new derivatizing matrix beyond the default (e.
Use when you have observed compounds (from LC-MS/MS, GC-MS, NMR, or other analytical techniques) with unknown identity and you want to assign candidate metabolite structures by…
Use when you have raw lipidomic and metabolomic data files generated by the Multi-ABLE method (high-pressure liquid chromatography–mass spectrometry output) and need to p — from…
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 when you have SWATH-MS raw data (mzML or vendor format) containing multiplexed MS/MS spectra from multiple co-eluting precursor ions and need to separate these spectra…
Use when working with untransformed metabolomics count data (e.g., c57_nos2KO_mouse_countDF)
Use when you have a 1D ¹H NMR spectrum (as chemical shift vs. intensity) and a corresponding peak list (chemical shift values), and you need to identify which metabolites are…
Use when after training a neural network or regression model to predict metabolomic profiles from microbiome data.
Use when after metabolite annotation has been completed (level-1 confidence via spectral library matching in margheRita or equivalent), and you need to perform pathway enrichment…
Use when after feature extraction (Asari) has produced a full feature table from mzML data, but before normalization and annotation.
Use when after drift correction has been applied to a MetaboSet object, and before imputation and batch correction.
Use when you have executed mzExacto() on a preprocessed GC-MS dataset and need to verify that the returned dataframe correctly matches query chemicals to their m/z peaks,…
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 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 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 you have raw untargeted LC/HRMS data (mzXML, mzML, or netCDF format) from population-scale studies (n > 500 samples) and need to extract a comprehensive peaklist with…
Use when you have an unknown compound's mass spectrum (m/z peaks and intensities) in . — from HolobiomicsLab/asb-skill-collections
Use when you have uploaded a pre-analytical data table containing sample metadata, processing timestamps (pre- and post-centrifugation), and NMR metabolomic measurements — from…
Use when you have a set of candidate transformed structures generated by biotransformation rules (e.
Use when you have a parent compound (or set of compounds) in SMILES, MOL, or SDF format and need to predict plausible metabolite structures and pathways in a specific biological…
Use when you have a raw LC–MS compound metadata file (xlsx or csv) with heterogeneous column names and column order, and you need to prepare it for targeted peak detection in…
Use when you have metabolomic data (e.g., from LC-MS or GC-MS comparing patient to controls) showing differential abundant metabolites (DAMs), candidate genes from exome…
Use when when your metabolomic network contains multiple edge types (Biochemical,
Use when after peak detection in untargeted LC/HRMS workflows, when you have a list of candidate peaks with signal intensity profiles and need to filter them according to data…
Use when you have raw untargeted LC/MS data in open mzML or mzXML format and need to extract a quantified feature matrix (m/z and retention time coordinates with sample…
Use when you have raw LC-MS data in mzML or equivalent binary format from a public repository (MetaboLights, MassIVE) or instrument vendor output, and need to ingest it into…
Use when you have untargeted LC-MS metabolomics data preprocessed with XCMS and need to filter out low-quality peak integrations that could introduce false positives or noise into…
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 after loading raw metabolomics data (e.g., from Metabolon, Nightingale,
Use when you have raw 1D NMR spectral data (urine, worm, or other biological samples) that needs to be converted into peak tables for metabolite identification and quantification.
Use when after you have detected LC-MS features, grouped them into empirical compounds via isotope and adduct clustering (using khipu), and have accurate m/z and retention time…
Use when your metabolomics dataset (LC/MS or GC/MS) contains missing values encoded as NA or zero that represent compounds below the instrument's limit of detection (LOD) or limit…
Use when your input is a raw metabolomics intensity matrix (compounds × samples) with known batch assignment and QC sample labels, and you observe signal drift across the…
Use when when you have cloned or accessed the Reverse_metabolomics_library_generation
Use when you have a raw metabolomics abundance table (e.g., LC/MS or GC/MS peak intensities or concentrations) with non-normal distributions and missing values, and you need to…
Use when you have a matrix of Nightingale Health 1H-NMR metabolomics measurements (samples × features) and need to generate predicted metabolic scores published in peer-reviewed…
Use when you have trained multiple machine learning classifiers (e.g., AdaBoost, SVM, Random Forest) on the same metabolomics peak-quality training set using k-fold…
Use when when benchmarking or validating a pathway analysis method (such as PALS, ORA, or GSEA) on metabolomics data, you need quantitative evidence that the method's pathway…
Use when you have a metabolomics dataset and want to perform pathway enrichment analysis using ORA, but need to first understand its behavior, limitations, and correct application…
Use when when preparing to process raw LC-HRMS metabolomics data (.mzML or .abf files) with MS-DIAL within a Nextflow pipeline, before executing peak detection and chromatogram…
Use when you have raw peak tables exported from a tandem mass spectrometry preprocessing tool (e.g. Progenesis, MS-DIAL, or Bruker Metaboscape) and need to integrate them with…
Use when you have acquired raw SIMS (secondary ion mass spectrometry) metabolite images aligned with tissue regions and segmented single-cell masks, and you need to extract…
Use when after batch correction of metabolomics data using pooled study quality control (SQC) samples and calculation of compound/internal standard ratios, when you need to decide…
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 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 when you have received Sciex Multiquant TXT export files from a completed metabolomics or lipidomics analytical run and need to verify that QC pool samples were injected…
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and b — from…
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and b — from…
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and b — from…
Use when when you have read LC-MS peak table data from Excel (or equivalent) into R and need to organize it into a structured object that tracks feature abundances, sample…