Use when your input is a corpus of MS/MS spectra with annotated molecular formulas and adduct types that represent a new ionisation mode, instrument type, or adduct chemistry not…
Use when you have received MSBERT-preprocessed spectral data from GNPS, MoNA, or MTBLS1572 and need to ensure data integrity before training a spectral embedding model.
Use when you have assembled genome sequences (contigs or scaffolds in FASTA format) and want to identify putative BGCs and their precursor peptides before constructing a RiPP…
Use when when you need to generate reproducible synthetic LC/GC-MS raw data files with known ground-truth peak properties (m/z, retention time, intensity) for benchmarking peak…
Use when a Shiny application or similar cross-platform tool is restricted to a single operating system (e.
Use when after peak detection and MS1 feature extraction from FIA-MS, GC-MS, LC-MS(/MS), or CE-MS data, when you need to identify unknown metabolites by matching observed m/z…
Use when your mass spectrometry DataFrame contains m/z, retention time (or mobility), and intensity columns, and you need to generate an interactive HTML figure for exploration,…
Use when after applying any sequence of spectrum preprocessing operations (set_mz_range, remove_precursor_peak, filter_intensity, scale_intensity) to an MsmsSpectrum object, to…
Use when when a project README or documentation embeds badge endpoints that report real-time status (e.g., Travis CI build, Landscape.
Use when you have a measured m/z value from spatially-resolved metabolomics or mass spectrometry imaging and need to assign a molecular formula with high confidence.
Use when when converting MS/MS spectra from .msp format library files (e.g., MassBank) into a custom fragment library for metabolite annotation, and the source spectra are tagged…
Use when you have Bruker NMR spectral files (raw instrumental output) and need to prepare them for automated metabolite identification and quantification.
Use when when rendering a treemap of qc_summary() output showing ion counts and percentages by filter status (passed/failed), and you need a perceptually uniform,…
Use when executing containerized conversion tools (e.g., AirdPro CLI) that must read vendor-format mass spectrometry raw files from the host filesystem and write converted output…
Use when you have a spatial transcriptomics dataset (AnnData object) with cell/spot coordinates and an associated tissue microscopy image file, and you need to compute…
Use when you have annotated MS/MS spectra in MGF format and need to identify peptide sequences that may not exist in reference protein databases—such as in immunopeptidomics,…
Use when after invoking the saveAnnotations function on a MetaboAnnotatoR annotations object to confirm that all four expected output file types (global results file, ranked…
Use when you have a peak intensity matrix from LC/GC-MS analysis with known QC sample indices and suspect batch-related systematic variation in feature intensities.
Use when you have imported a raw GCxGC-MS chromatogram (NetCDF format folded into 2D-TIC) that exhibits chemical noise, instrumental artifacts, or baseline drift—conditions that…
Use when after converting mass-spectrometry data from an existing format (mzML, mzXML, or vendor-specific formats) into mzPeak using command-line tools or API calls.
Use when when constructing a sample list from an Excel template for LC/GC-MS analysis, you must classify each QC sample by type before proceeding to plate layout and randomization…
Use when you have loaded normalized methylation beta-value matrices from Illumina EPIC or 450k arrays and need to move beyond single-CpG differential methylation testing to…
Use when you have completed LC-MS/MS data processing and feature alignment in MZmine2 or Optimus, generated a feature quantification matrix and MGF file, and now need to format…
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 a preprocessed feature table from non-targeted LC-MS/MS metabolomics data (after data merging, cleanup, blank removal, and batch correction) and need to test…
Use when you have a pre-trained GNN model for CCS prediction and need to verify that it generalizes to test data that was held out during training.
Use when after running do.findmain on a RAMClustR-clustered object to infer molecular weights and assign features to compound clusters, when you need to conduct structural…
Use when you have a query electron ionization (EI) mass spectrum and need to search it against a library of known EI mass spectra to identify unknown compounds.
Use when you have extracted peaks from multiple LC/HRMS batches (n > 500 samples across different analytical runs or days) and observe systematic retention time drift or offset…
Use when apply CLR transformation when you have microbiome or metabolomic count data that sums to a constant across samples (relative abundance or compositional data) and intend…
Use when when evaluating a new or updated version of a data processing tool (especially asari or similar LC-MS workflows) before production deployment, or when verifying claims…
Use when you need to validate that a published software tool (e.g., MassQL) executes correctly in your environment, reproduce published results, or contribute to development.
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 you have an annotated or raw tandem mass spectrometry spectrum and need to identify which observed peaks correspond to expected peptide fragment ions from a known or…
Use when after constructing individual mass tracks from mzTree data bins and before alignment across samples.
Use when your peak table includes features flagged in blank control samples (e.g., solvent blanks, media blanks) at relative abundance above a project-specific threshold.
Use when you have a Python webservice codebase (e.g., a Flask, Django, or FastAPI application) and need to document its HTTP API surface (endpoints, methods, parameters, schemas,…
Use when you need to validate that a repository's automated build and publish pipeline is functioning correctly on a release or target branch, particularly when assessing the…
Use when when you need to empirically validate that one mass spectrometry data processing library achieves higher throughput than competing alternatives.
Use when you have ranked GCF-MF (Gene Cluster Family–Molecular Family) links using two or more independent scoring functions and a set of experimentally validated links.
Use when you have inferred or discovered structured results (e.g., LDA-derived motif sets with mass compositions, neutral-loss patterns, and ranked database matches) that must be…
Use when training embeddings from MS/MS spectra and you need to simultaneously enforce: (1) discrimination between spectra with different structural properties via contrastive…
Use when you have generated or assembled a lipid spectral library with precursor m/z values, adduct information, and fragmentation patterns, and you need to import those spectra…
Use when when you have raw mass spectrometry data from direct-infusion (DI-MS) or ambient surface analysis probe (ASAP-MS) instruments and need to identify which m/z peaks are…
Use when when you have validated SMILES strings or canonical molecule objects from RDKit and need to convert them into the fixed-size numerical tensor format expected by a deep…
Use when your input is a single-cell gene expression matrix too large to fit in RAM, or you are working in a resource-constrained environment (e.g., shared compute cluster, laptop…
Use when when comparing large numbers of MS/MS spectra against spectral libraries or in molecular networking, particularly when molecules differ by multiple structural…
Use when after cloning or installing a peak-calling or genomic analysis tool from a repository, before using it on production data.
Use when analyzing RNA-seq count data from a DESeq2 workflow where you have fitted negative binomial generalized linear models and need to extract final results.
Use when you have pre-trained Keras models from the NP-Classifier repository that must be deployed via TensorFlow Serving and need to expose standardized input/output layer names…
Use when when implementing an igzip parser, decoder, or validator that must interpret the custom header format; when debugging igzip file corruption or encoding errors; or when…
Use when when you have raw TWIM-MS arrival-time data and need to transform it into absolute CCS values for downstream biomolecular class assignment or comparative analysis.
Use when after MamsiStructSearch has completed structural clustering of statistically significant LC-MS features (p < 0.
Use when after executing feature detection and quantification on raw LC-MS data (mzML or NetCDF format) using an automated pipeline such as MetaboAnalystR 4.0, and before…
Use when when you have obtained a raw Orbitrap mass spectrometry file and need to verify that the instrument was configured as claimed in the methods section or dataset…
Use when after mass track construction and before composite map building, when you need to align retention times across multiple LC-MS samples.
Use when when you have SMILES strings representing neutral organic molecules and need to enumerate the likely protonated (e.g., [M+H]+) and deprotonated (e.
Use when you have preprocessed 1H NMR spectral data (e.g., from plasma or biological samples acquired on a 600 MHz instrument) and need to identify the chemical composition of a…
Use when after feature detection and quality control have produced a feature table in TSV format from Asari or equivalent preprocessing.
Use when your metabolomics experiment includes samples acquired across multiple instrument runs, different preparation dates, or distinct sample cohorts.