Use when after preprocessing and normalizing count matrices from transcriptomics
Use when when beginning an LC-MS/MS metabolomics analysis pipeline and you have preprocessed xcms result objects (XcmsExperiment or legacy xcmsSet) that need to be loaded into…
Use when you have two MemoMatrix objects generated from separate sample cohorts (e.
Use when after you have accumulated experimental MS data from ≥2 LC gradient trials, extracted separation efficiency metrics (retention time spacing) from each trial, and encoded…
Use when you have raw or preprocessed MS imaging data archived as an RDS file or from a Zenodo deposit that includes the full m/z feature set (e.g., 10,200 m/z values spanning…
Use when when you have a spatial molecular dataset (e.g., Visium, MERFISH) with categorical cell-type or feature annotations and want to test whether specific categories are…
Use when you have completed NMR data quality control analysis and possess per-feature CV values, and you need to formally assess whether the metabolomic dataset meets FDA…
Use when when you have raw molecular structures in SMILES or SDF format that must be prepared as input to a descriptor-based classifier (e.g., BitterPredict).
Use when you have an aligned feature table from untargeted LC-MS with missing intensity values (NA or zero entries) for features that are present in some samples but fell below…
Use when you have centroided LC- or GC-HRMS data (in mzML format, ideally from data-dependent acquisition) and need to identify potential PFAS candidates from a large feature list.
Use when after peak picking, sample alignment, and isotopologue/adduct grouping are complete, and you have DDA-MS2 scans associated with grouped feature ions.
Use when when building a neural network to map between mass spectrometry spectra and molecular properties (e.g., fingerprints, SMILES, or fragment ions) where sequential or…
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 you have extracted mass tracks (EICs) from multiple LC-MS samples aligned into a MassGrid structure, and you need to combine their intensity vectors into a single…
Use when when building a transformer-based model to process mass spectrometry data (MS/MS spectra or fingerprints) where you need the model to learn multiple independent attention…
Use when you have a Thermo Fisher Orbitrap .raw file and need to recover the intensity profile of a specific m/z value or peptide across the LC separation dimension…
Use when after nontargeted peak detection has identified candidate peaks in LC-MS chromatograms, when you need to establish exact peak start/end retention times and extract…
Use when when you have an unknown MS/MS spectrum (with ≥10 peaks, precursor m/z, and at least 5 fragment ions) and need to identify it by comparing against a curated spectral…
Use when after instantiating and invoking a sinusoidal formula embedding layer (such as SCARF embeddings in MIST-CF) on chemical formula inputs, validate that the output…
Use when you have a pair of MS/MS spectra—one from a known compound and one from a structurally related modified (unknown) compound—and need to identify which atom(s) in — from…
Use when after filtering duplicate reads from ChIP-Seq data but before generating pileup coverage tracks.
Use when after using edgeR::DGEListFromTximport with divide=TRUE on tximport output containing Gibbs sample or bootstrap replicates.
Use when you have multiple CDF files containing mass spectrometry imaging data (spectra, m/z arrays, and spatial coordinates) that need to be ingested into MATLAB for the DIMPLE…
Use when you have centroided LC-MS/MS spectra (in MGF, mzXML, mzML, or mzData format) and wish to identify peptidic natural products or ribosomally synthesized and post-t — from…
Use when when you have a webservice codebase (Python, Java, etc.) with HTTP route definitions, parameter handling, and serialization logic, and you need to generate an OpenAPI 3.
Use when you have Spectra::Spectra objects in R and need to apply Python MS algorithms from matchms or spectrum_utils (e.g., CosineGreedy similarity scoring, normalization, or…
Use when you have preprocessed MS/MS spectra (noise-filtered, normalized) and need to compute pairwise similarity or distance scores for compound library matching, when your goal…
Use when when you have antiSMASH-predicted BGCs and wish to link them to metabolomic data via structure prediction, but only BGCs with sufficient structural homology to…
Use when when you have preprocessed mass spectrometry imaging (MSI) ion images and need to generate augmented image pairs for contrastive learning in co-localized ion discovery…
Use when you have an unknown electron ionization (EI) mass spectrum and need to identify the compound by comparing it against a reference library (msp file format).
Use when when you need to validate that MSI software (e.g., LipidQMap) achieves documented processing speeds on your target hardware, or when you need to establish a performance…
Use when when you have query chemicals identified by GC-MS (with Match.Factor values) and need to verify structural similarity against a reference chemical library to confirm…
Use when you have an MS/MS peak list and need to remove electronic noise—specifically
Use when after XCMS peak picking and fillPeaks() when you have xcmsEIC and filled xcmsSet objects and need to systematically flag low-quality or unreliable peak integrations prior…
Use when after Casanovo has generated ranked peptide sequence predictions from MS/MS spectra and you need to persist, share, or integrate the results into a proteomics data…
Use when you have aligned ATAC-seq BAM files and peak annotations from two or more experimental conditions (e.
Use when you have raw mass spectrometry imaging data (2D or 3D spatial coordinates with full mass-to-charge spectra) and want to train a probabilistic deep learning classifier for…
Use when after generating normalized dense embeddings for both query and reference MS/MS spectra using a pre-trained model like SpecEmbedding.
Use when after performing assignment operations (assign_ri, assign_smiles) or combining multiple library objects (e.
Use when a Python-based metabolomics analysis package has been relocated to a new GitHub organization (e.g., metabolomics-cloud) and you need to confirm that the migration…
Use when you are developing or comparing new data-dependent acquisition (DDA) strategies in ViMMS and need to evaluate how well each strategy fragments sampled compounds from the…
Use when you have raw or preprocessed MS/MS spectra in one of the supported formats (MGF, mzML, mzXML, JSON, MSP, mzXML, pickled matchms objects, or USI) and need to extract peak…
Use when after performing isotopic correction, quantitation, or other pixel-level transformations on a feature-by-pixel intensity matrix imported from an imzML file via Cardinal's…
Use when you have a set of training LC-HRMS chromatograms (retention time × m/z matrix format) and a manually curated reference list of isolated single chromatographic peaks, and…
Use when you have NMR-based metabolomics measurements from a cohort containing both plasma and serum samples with associated processing delay metadata (pre- and…
Use when you have raw LC/MS data in mzML format and need to execute a complete non-targeted screening workflow to extract and annotate chemical features.
Use when after calling peaks and annotating cells in an ArchR project, when you need to perform trajectory analysis using STREAM or other external tools that require a…
Use when when beginning an untargeted LC-MS metabolomics study and need to assemble a cohort of mzML files for processing; particularly when establishing performance baselines…
Use when when a trained Siamese neural network model makes predictions on new spectrum pairs and you need to identify and exclude high-uncertainty predictions to improve RMSE.
Use when when applying a series of mpactr filter functions (filter_mispicked_ions,
Use when you have raw Hi-C FASTQ data and need to generate contact maps at kilobase resolution, or you have pre-generated .hic files and need to annotate structural features…
Use when you have raw arrival-time data from TWIM-MS and need to convert it to collision cross section (CCS) values for multi-omic analysis.
Use when after executing a molecular structure prediction model on spectroscopic
Use when when you need to enable users to express complex mass spectrometry search patterns (e.
Use when you have MSI intensity data exported from MSiReader, SCiLS, or Cardinal as plain-text CSV files or as Cardinal MSProcessedImagingExperiment/MSContinuousImagingExperiment…
Use when you have a .msp spectral library file with sparse or incomplete metadata (e.
Use when deploying the ipbhalle/metfragweb container and you need to supply custom MetFrag settings (ChemSpider tokens, proxy servers, local database connections) without…
Use when you have LC-HRMS chromatograms in retention time × m/z matrix format and need to automatically localize chromatographic peak positions and extents prior to matching…
Use when when you have extracted feature tables from multiple breath samples (mzML/mzXML files) using feature extraction, and you need to identify which features are the same…
Use when you have aligned ATAC-seq BAM files from Tn5-based chromatin accessibility assays and need to perform footprinting analysis.