Use when you have raw LC/MS data in mzML format and need to perform non-targeted
Use when you have UPLC-HRMS raw data (ThermoFisher, Agilent, or compatible vendor format) from water samples or environmental matrices containing unknown organic pollutants, a…
Use when when you have access to a peer-reviewed manuscript with an accompanying
Use when after obtaining 512-dimensional representation vectors from the Encoder module, when you need to compress these vectors for visualization, clustering, or downstream…
Use when you have CE-MS test files archived in the msdata Bioconductor package and need to load them into an in-memory or on-disk R representation to extract ion…
Use when after RAMClustR clustering of XCMS-detected features and prior to final compound annotation, when you need to verify the robustness of molecular weight inference or when…
Use when you have paired measurements (e.g., gene expression counts, protein abundance, or sampled flux distributions) from two cell lines or conditions and need to assign a…
Use when when you have constructed a two-layer metabolite annotation network (knowledge-driven and data-driven) and need to propagate initial seed annotations (e.
Use when after peak detection in GC-IMS preprocessing, when you need to group peaks across multiple samples and must decide whether euclidean distance is appropriate for your…
Use when you have raw CE-MS data (mzML or netCDF format) with migration time measurements and need to establish a reproducible compound-specific axis that is independent of…
Use when after constructing a NetworkX graph object from structural clusters (via MamsiStructSearch), when you need to interactively explore feature relationships or publish a…
Use when when you have extracted ion chromatograms (XICs), ion mobilograms (IMs), or mass spectra from diaPASEF or other DIA workflows and need to visualize them interactively to…
Use when you have raw LC-MS/MS spectra from vendor instruments (mzML, mzXML, MGF, or MSP format) with variable peak quality and intensity distributions, and you plan to perform…
Use when you have metabolomics intensity data with peak annotations, and you want to rank and prioritize metabolite groupings (Molecular Families, Mass2Motifs, or other…
Use when after performing an ANOVA-style multi-group de_design() analysis on a LipidomicsExperiment object, when you need to determine whether a categorical sample variable (e.g.,…
Use when when processing CE-MS test files and you need to identify and extract the migration time of the EOF marker (e.g., Paracetamol) to normalize compound migration times…
Use when you have acquired complementary spectroscopic measurements (NMR, HSQC, COSY, IR) for the same molecular sample and need to combine them for structure elucidation.
Use when when you have known metabolite concentrations and their spin-system coupling constants (J-values) and need to generate synthetic ¹H NMR spectra for method validation,…
Use when when you need to reconstruct or validate the control-flow architecture of a spectral search system that must handle both exact-match library lookups and analogue…
Use when after blank masking and sample dropping, when you have a feature table with intensity values that exhibit systematic variation across sample collection batches or…
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 processing LC-MS/MS data acquired in DDA mode that contains chimeric (co-fragmented) MS/MS spectra—i.e., when a single MS/MS scan contains fragments from multiple…
Use when you are setting up HiC-Pro or a similar multi-tool pipeline for the first time, or you need to validate that all required dependencies are installed and discoverable.
Use when you have a processed single-cell expression matrix (AnnData object) with pre-computed cluster assignments (e.g., leiden or louvain clusters in adata.obs) and want to…
Use when a paired omics project JSON document contains genome identifiers (e.g. IMG IDs, NCBI accessions) but lacks corresponding organism names.
Use when when you have computed similarity scores (cosine, modified cosine, Spec2Vec, or other metrics) between a set of query spectra and a reference library with known…
Use when when preparing paired MS/MS spectra for training or validation of a siamese neural network model, and you have chemical structure annotations (InChI, SMILES, or InChIKey)…
Use when you are performing dimensionality reduction on a sparse single-cell count matrix (in CSR format) and need to compute pairwise cell similarities before spectral…
Use when you have a raw NV (NMRViewJ) binary file and need to confirm it is well-formed before parsing or processing.
Use when preparing mass spectrum input tensors for transformer encoder layers in IDSL_MINT.
Use when when you have a labeled peak quality matrix (with known pass/fail labels), need to objectively compare performance across multiple classification algorithms (e.
Use when when building a file I/O abstraction layer that must support multiple serialization formats (e.g., uncompressed mzML, gzip-compressed mzML, indexed gzip mzML, or…
Use when after applying a quantitative analysis function (e.g., cooltools.insulation, contact frequency calculations) to Hi-C cooler files or other genomic datasets, validate that…
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 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 you need to understand how a data-processing software system discriminates among multiple input types (LC, GC, IMS, MALDI) and selectively instantiates processing…
Use when when you need to confirm that a generated or retrieved release artifact from a version control system (e.g., git tag v1.0.0) produces byte-for-byte or functionally…
Use when you have extracted raw tabular metadata into JSON form using the MESSES extract command and need to confirm the extraction is accurate before conversion to a…
Use when you have an unknown mass spectrum (or a representative metabolite spectrum from public data) and need to identify it by comparing it against a large reference…
Use when you have raw molecular structures in SMILES or SDF format that will feed into BitterPredict.m or other structure-based classifiers.
Use when after feature detection and alignment on raw MS data, when you have a list of unknown feature m/z values and need to assign them to known xenobiotic metabolites or their…
Use when you have extracted MS1 and MS2 scans (in mzML/mzXML format) from raw chromatogram files and possess user-provided metadata (retention time, m/z, compound name, m — from…
Use when when you have trained a candidate model (e.g., an ensemble, a new architecture) and need to demonstrate its advantage over published or reference implementations on the…
Use when you have tabular data (CSV or Excel) with column headers annotated using MESSES tagging syntax (#<table_name>.id for record identifiers, #.
Use when you have raw peak area or intensity measurements for both compounds and their corresponding internal standards across all study samples (including QC and calibration…
Use when you have paired microbiome (16S rRNA, metagenomic) and metabolomic (LC-MS, GC-MS) abundance tables from the same biosamples, and you want to predict which metabolites are…
Use when you have a trained multitask machine learning model for structure prediction, test set molecules with paired ¹H and ¹³C NMR spectra, and need to understand the marginal…
Use when after applying mspcompiler pipeline transformation steps (e.g., reorganize_mona, assign_smiles, assign_ri, read_multilibs, separate_polarity, complete_mgf) to confirm the…
Use when after training a customized R statistical or machine learning model on annotated training data, you need to persist the trained model object for reuse in downstream…
Use when you have RNA-seq read count data (from alignment tools, transcript quantification, or feature counting) organized in a count matrix with samples as columns and genes as…
Use when you have a GNPS-generated classical or feature-based mass spectral molecular network (graphml or JSON format) and a corresponding MS2LDA experiment with Mass2Motif…
Use when when you have a spatial metabolomics or LC-MS dataset with detected m/z features (as a feature matrix or SpaMTP Seurat object) and need to assign metabolite identities.
Use when you have two augmented versions of the same ion image (from mass spectrometry imaging data) and need to extract learnable 512-dimensional feature representations using a…
Use when when you have loaded an unprocessed Cardinal object from MS imaging data (e.g., from Zenodo or native formats) containing thousands of m/z features across many spectra,…
Use when you have custom lipid entries (e.g., synthetic lipids, rare natural variants, or isotopically labeled standards) not covered by LipidMatch's default in-silico library,…
Use when when you have trained multi-layer perceptron neural network models on paired microbiome-metabolome data (from ≥10-fold cross-validation iterations) and need to identify…
Use when you have GC-MS data with multiple replicate injections or samples, need to identify a predefined set of query chemicals by name, and want to consolidate all instances of…
Use when when you need to execute a multi-backend visualization library (e.g., pyOpenMS-Viz with matplotlib, Bokeh, and Plotly) and must measure or validate execution times,…
Use when after frequency-based denoising of MS/MS spectra, when you need to validate that denoising improves metabolite identifications and quantify the trade-off between signal…
Use when after organism name cleaning and taxonomy verification (4_cleaningTaxonomy.R) have been completed and you have a cleaned organism table with standardized names.