Use when when you have preprocessed LC-MS/MS data (MGF file with MS1 and MS2 spectra and a feature abundance table from MZmine2 or similar peak detection tool) and need to perform…
Use when you have a pre-trained GNN CCS prediction model and need to assess its predictive performance and cross-dataset generalizability.
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 when you have pre-computed Word2vec spectrum embeddings and need to perform fast approximate nearest-neighbor retrieval from a library of millions of spectra (e.g., NIST…
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 contributing code changes to a Python project (fork, feature branch, or pull request) that uses a setup.py-based test suite, before pushing changes to the remote…
Use when you have completed independent batch searches across one or more domain-specific MASST tools (microbeMASST, plantMASST, tissueMASST, microbiomeMASST, foodMASST) and…
Use when you have ATAC-seq BAM alignments with classified motif sites (bound vs. unbound based on chromatin accessibility or binding thresholds) and wish to detect and visualize…
Use when you have a pretrained model with documented performance on a bounded input domain (e.g., molecules ≤19 heavy atoms, sequences <1000 bp) and you need to establish whether…
Use when when you have run a spectral networking job on GNPS (e.g. ProteoSAFe-METABOLOMICS-SNETS-V2) and need to reuse the network output files locally with MetaMiner or another…
Use when you have BioTransformer-predicted metabolite structures (in SMILES or InChI format) and need to identify which known compounds in public databases match those structures.
Use when you have a validated ReDU sample-information metadata table (gnps_metadata.tsv) loaded from a MassIVE accession, and you need to partition public MS/MS files into…
Use when when preparing NMR datasets for processing in NMRFx and the Dataset.createDataFile() method must choose among competing storage backends.
Use when when you have received raw MRM lipidomics export files in vendor-specific
Use when you have a mass spectrometry visualization library that claims to support multiple plotting backends and need to verify that: (1) all backends produce functionally…
Use when you have long-read RNA-seq samples quantified by oarfish (output as quant.gz files) and need to extract transcript-level or gene-level abundance, count, and length…
Use when you have untargeted metabolomics data with unknown or ambiguous molecular identities, anchor metabolites (known structures in SMILES or MOL format), and a curated…
Use when when evaluating a regression or similarity prediction model and you need to understand whether prediction error is uniform across the outcome space or concentrated in…
Use when you have constraint-based metabolic models with integrated multi-omics constraints (transcriptomics via Reaction Activity Scores, extracellular flux ratios via YSI…
Use when when you need to reproduce or validate a specific historical release artifact (e.g., a Semantic Release v1.0.
Use when immediately after loading raw methylation array data (.idat files or beta-valued matrix) from HumanMethylation450 (450k) or EPIC arrays when conducting primary quality…
Use when when annotating m/z features from Cardinal MSImagingExperiment objects or LC-MS datasets against metabolite databases (HMDB, Lipidmaps) and you need to exclude matches…
Use when you have raw CE-MS or LC-MS instrument files (stored as OnDiskMSnExp objects or similar Bioconductor containers) and need to extract quantitative features (migration…
Use when you have computed raw p-values from partial Spearman correlations (or other univariate tests) between each metabolite in a SummarizedExperiment object and a phenotype of…
Use when after autoQ has extracted isotopologue peak area measurements from mz(X)ML files and you need to prepare the integrations data frame for visualization with metBarPlot or…
Use when you have raw MS/MS spectra in MGF or other standard formats that need to be ingested into a machine learning pipeline for cross-modal matching against molecular…
Use when when you have retention times measured on one chromatographic method and need to predict or map them to another method with minimal or no overlap in measured molecules.
Use when after AutoTuner has completed EICparams extraction and parameter estimation on raw untargeted metabolomics data (mzML, mzXML, or CDF format), and you need to pass those…
Use when you have developed a new machine learning model for predicting metabolomic profiles from microbiome data and need to quantify its performance improvement over existing…
Use when when you have received or cloned a CCS reference library (such as the DTCCSN2 library for U13C labeled lipids) bundled with lipidomics software and need to verify its…
Use when you have a methylDiff object containing differentially methylated bases or regions from bisulfite sequencing, gene annotation in BED or similar format (RefSeq, Ensembl),…
Use when you have MS imaging or LC-MS data with pre-annotated m/z values that include multiple isomer or metabolite names per m/z (stored as semicolon-delimited or multi-record…
Use when after peak filtering and normalization, when you have a peak-abundance matrix (samples × assigned molecular formulas) and need to visualize and test for differences in…
Use when you have a pre-generated .hic contact map file and need to identify and annotate chromatin loops or topologically associating domains (TADs) at high resolution.
Use when when you need to extract m/z and intensity peak values from a Spectra object backed by MsBackendMzR or similar on-disk backends; when analyzing subsets of spectra without…
Use when you have computed a sparse pairwise distance matrix from MS/MS spectra (via nearest neighbor indexing) and need to partition spectra into homogeneous clusters—typically…
Use when when clustering large-scale mass spectrometry datasets (millions of MS/MS spectra in MGF format) where runtime is a bottleneck and you have access to NVIDIA GPU resources…
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 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 aligned feature tables (CSV format) paired with MS2 spectral data (MGF or mzML files) and need to compare chemodiverse samples with poor feature overlap or…
Use when you have centroided MS2 spectra (in mzML format from data-dependent acquisition) and a list of known or suspect PFAS diagnostic fragment masses, and you need to…
Use when after implementing or modifying the scoring module that computes average InChIKey scores and neighbourhood scores for candidate matches, or when integrating new scoring…
Use when when you have paired mass spectra and molecular structure data and need to train a model that can bidirectionally map between experimental spectra and chemical s — from…
Use when you have a GNPS mass spectral molecular network (in graphml or cytoscape format) and want to enrich its nodes with chemical class information derived from GNPS public…
Use when you have GC–MS data from human breath samples and need to identify marker metabolites for disease diagnosis, phenotyping, or biomarker discovery without a predefined…
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 preprocessed single-cell RNA-seq data (normalized and dimensionality-reduced via PCA) and need to establish cell-to-cell connectivity for trajectory inference,…
Use when when you have access to a set of gallery or benchmark scripts executed across multiple plotting backends and need to quantify which backend delivers the fastest median…
Use when you have extracted latent low-dimensional peak features from imaging mass spectrometry (IMS) data using a graph-attention autoencoder and need to identify a ranked subset…
Use when a web application receives mass spectrometry data through heterogeneous
Use when you have a feature list with m/z values from HRMS data and need to identify homologous PFAS series to prioritize suspect screening.
Use when after peak detection in GCIMS when you need to group detected peaks across multiple samples into reproducible clusters.
Use when you have molecular identifiers (SMILES strings or molecular structure files) that need to be converted into node-edge graph tensors for input to message passing neural…
Use when you have normalized peak-abundance matrices with sample metadata containing categorical treatment variables (e.
Use when when you have ionized adduct structures (in SMILES or MOL format) from an upstream ionization-state determination step and need to produce multiple low-energy 3D…
Use when you have raw or processed HRMS/MS data from Q-Exactive, Agilent Q-TOF, Bruker Q-TOF, or SCIEX Q-TOF instruments in formats such as mzML, CSV peaklists, or vendor-specific…
Use when you have loaded a collection of molecular fingerprint vectors (such as biosynfoni fingerprints from a deposited dataset) and need to characterize their statistical and…
Use when when you have aligned peak-alignment data from a preceding molecular networking task (structured as a table with peak intensity, m/z, retention time, and alignment…
Use when you have raw SMILES strings from multiple external database sources (e.g., PubChem, ChEMBL, vendor databases) that need to be integrated into a unified structure…
Use when when you have extracted concatenated MS/MS spectra for multiple features from replicate mzML files and need to verify that a TIC-based filtering step (e.g., top x% TIC…