Use when you have computed raw strain correlation scores and IOKR scores for the same set of GCF–MF (gene cluster family–molecular feature) pairs, and you want to compare or…
Use when when you have a binned MS/MS spectrum vector (e.g., 9948-dimensional input from 10,000 equally-spaced m/z bins in the 10–1000 Da range) and need to compress it into a…
Use when when a statistical method offers a parameter to trade computational cost for precision (e.
Use when you have sequential QCpool (pooled quality control) samples analyzed with Sciex Multiquant (≥v3.0.
Use when after converting a decision tree path into a MassQL query string, before deployment to production mass spectrometry workflows.
Use when you have raw or unstructured MS2 spectral data (from untargeted tandem mass spectrometry experiments) and plan to run MS2MP inference for KEGG pathway prediction.
Use when you need to verify that a GitHub Actions workflow (such as dev_build_release.yml) successfully completes end-to-end, especially after code changes or to confirm that…
Use when when you have IM-MS lipidomics data spiked with U13C labeled lipid internal standards (e.g., fully labeled yeast extract) and want to assess whether measured CCS values…
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 when processing raw chromatography–mass spectrometry data (GC–MS or LC–MS) as a 2D m/z vs retention time map and you need to identify and visualize marker features for…
Use when you have a set of candidate metabolites for an unknown compound detected in a liquid chromatography–mass spectrometry (LC-MS) experiment, predicted RTs from a trained DNN…
Use when you have LC-MS metabolomics data in positive ionization mode and have already performed XCMS feature detection and RAMClustR clustering.
Use when when you have predicted MS/MS fragments from quantum chemistry calculations on N-Me derived unsaturated sterol structures and need to map each fragment to its precursor…
Use when you have a preprocessed LC-MS peak table exported from peak-picking software (e.g., MS-DIAL) in Excel format with three logical compartments: sample annotation (rows),…
Use when when you have parallel mass spectra and molecular structure data (e.g., CANOPUS or MassSpecGym datasets) and aim to train a single encoder-decoder model (e.g., BART) that…
Use when when preparing raw MS/MS spectra for input to a Siamese neural network trained to predict structural similarity scores (Tanimoto).
Use when you have a mass-spectrometry query string written in MassQL (or similar domain-specific SQL-inspired syntax) that must be converted into structured form for execution.
Use when you have translated or raw SMILES strings from a chemical structure curation pipeline and need to remove invalid chemical structures, resolve sanitization errors (e.
Use when after identifying a set of differentially accessible peaks (via tl.diff_test or equivalent), when you need to infer which transcription factors may regulate the observed…
Use when you have antiSMASH v5.0.0 BGC predictions from a set of microbial genomes and you need to integrate those predictions with GNPS metabolomic data (MS2 spectra and…
Use when a GitHub repository displays a CI workflow badge (e.g., passing/failing status in README) and you need to verify that the reported status is accurate, reproduce the CI…
Use when you have pre-processed chromatin accessibility data (ATAC-seq or DNAse-seq) with chromVAR deviations already computed for individual cells or bulk samples across multiple…
Use when analyzing raw 2D MS data (m/z vs. retention time maps) where conventional peak picking introduces unacceptable error rates, particularly in untargeted metabolomics or…
Use when when you have binned mass spectrometry imaging peaks and want to understand which detected mass-to-charge ratios represent the same metabolite in different ionization…
Use when you have a query mass spectrum and a set of candidate molecular structures, and you need to prioritize candidates by their likelihood of matching the query.
Use when after instantiating a transformer encoder module for mass spectrometry data processing (e.g., in IDSL_MINT), before training on large MS/MS datasets or running inference…
Use when after drift correction of LC-MS peak intensity data, when you need to identify metabolic features with excessive internal spread (within-group variability in QC samples)…
Use when after detecting local-maxima in LC-HRMS profile mode datasets and before training or inference with a CNN model for peak classification.
Use when you have located a workflow definition file (YAML or JSON) from a versioned release and need to confirm that all mandatory workflow metadata fields (name, version,…
Use when after converting MS/MS spectra to fixed-length vector representations using a pre-trained Word2Vec model (as in Spec2Vec), filter spectra before computing similarity…
Use when when you have an untargeted metabolomics feature table (m/z values, retention times, intensities) and aim to predict functional pathway activity without explicit — from…
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 you have validated intermediate JSON data (conforming to the Experiment Description Specification) and need to configure how it should be converted to a supported output…
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 have encoded spectral features (from a CNN featurizer applied to 1D 1H and/or 13C NMR spectra) and a set of candidate molecular fragments predicted for a…
Use when after loading a feature table into memory when the table contains zero or missing values that represent true signal loss (not genuine absence), and you need to impute…
Use when when applying a pre-trained Word2Vec model to mass spectra at inference time (e.g., library matching or molecular networking), especially when the query spectra may…
Use when you have downloaded raw HMDB data (hmdb_metabolites.zip or pickle file) and need to generate a representative set of chemical objects for simulating LC-MS/MS acquisition…
Use when you have a GNPS-generated molecular network (either classical or feature-based) and corresponding MS2LDA experiment output containing Mass2Motif-to-spectrum assignments,…
Use when you have PSI (percent-spliced-in) matrices calculated independently for two or more biological conditions, each with two or more replicate samples, and you want to…
Use when you need to automate testing and quality checks on code changes—specifically when pull requests or commits are made to a repository and you want to verify that builds…
Use when when you have raw mass spectrometry data (from mzML, Bruker .d, or CSV format) loaded into a Pandas DataFrame and need to ensure it has the correct column structure (m/z,…
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 you have centroided LC-MS/MS spectra (in MGF, mzXML, mzML, or mzData format) and genomically-predicted precursor peptide sequences, and you need to identify whic — from…
Use when when evaluating how well mass spectral similarity scores correlate with actual chemical structure for annotated spectral pairs (e.g., spectra with InChIKey metadata).
Use when you have raw Bruker NMR spectral files (from a Bruker instrument) in a directory and need to prepare them for automated metabolite identification and quantification using…
Use when after generating collision cross section predictions on a validation or test set using a trained graph neural network model, and you need to quantify prediction accuracy…
Use when converting MS/MS spectra into Spec2Vec embeddings using a pre-trained Word2Vec model that was trained on reference data (e.g., a subset of GNPS or MassBank).
Use when after parsing a MassQL query string into an abstract syntax tree or intermediate representation, before executing it against mass spectrometry data files (mzML, mzXML,…
Use when when performing ChIP-Seq peak calling with MACS3, after duplicate filtering and fragment length prediction (d), to construct the background model that will be compared…
Use when you have received a validated dataset (e.g., interim/tables/4_analysed/platinum.tsv.
Use when when you have predicted retention times from a DNN model trained on one chromatographic method (CM) and need to rank or filter metabolite candidates on a different…
Use when you have mass spectrometry MS/MS spectral data in GNPS-style MGF format and need to feed it into the Mass2SMILES deep learning model for structure and functional group…
Use when when you have a training set of MS2 spectra with known chemical structures (e.
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 clustered single-cell RNA-seq data (via Leiden, Louvain, or equivalent) and a k-nearest neighbor graph computed in PCA space, and you want to abstract cell-level…
Use when your ChIP-Seq input is paired-end sequencing data stored in BEDPE format (e.g., CTCF_PE_ChIP_chr22_50k.bedpe.gz), and you need to estimate fragment length and call peaks…
Use when you have multidimensional MS data converted to MZA HDF5 format (from Agilent .d, Bruker .d with ion mobility, Thermo .
Use when you have peak-picked LC-MS metabolomics data in a tabular format (R data frame) with columns for mass-to-charge ratio, retention time, feature identifiers, adduct…
Use when you have a feature intensity matrix (peak vector) and a corresponding set of QC sample indices from a multi-batch LC/GC-MS experiment, and you need to establish…