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 a trained regression model (e.g., a neural network or similar predictor) and a held-out test set with ground-truth continuous labels, and you need to measure…
Use when after identifying differentially methylated bases or regions (via calculateDiffMeth() and getMethylDiff()), when you need to characterize WHERE these methylation changes…
Use when after running saturation repair or multidimensional smoothing on IM-MS data when you need to validate whether corrected peaks are reliable or whether overlapping…
Use when you have a filtered peak list (CSV with m/z values and assigned molecular formulas) from FT-ICR MS and want to infer biochemical transformations occurring in microbial or…
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 received raw CE-MS or LC-MS output files in vendor-specific formats from a mass spectrometry instrument and need to process them through an untargeted…
Use when you have raw quantification data (abundance or intensity values across samples and features) from mass spectrometry or similar high-dimensional assays and need to prepare…
Use when you have raw IM-MS data (Agilent MassHunter .d or UIMF format) and need to exclude early or late chromatographic regions—e.g., to skip dead volume, exclude blank runs,…
Use when when performing targeted peak detection on LC-MS data where compounds have been assigned expected ionization polarities (positive or negative mode) in the target list,…
Use when after generating cross-spectrum negative examples via precursor m/z windowing and before training a rescore model (e.g., Siamese architecture in FIDDLE v2.0.0).
Use when when you have a list of chemical compounds (with m/z values, retention times, and intensities) and need to simulate their acquisition behavior under a specific ionization…
Use when when you have preprocessed MS/MS spectral data (filtered, noise-reduced,
Use when when calling filter functions (e.g., filter_mispicked_ions(), filter_group(), filter_cv()) on R6-based metabolomics data objects in the mpactr package and you need to…
Use when when beginning ChIP-Seq analysis with single-end BED/SAM input and no prior knowledge of the library's fragment length.
Use when you have access to a lipidomics library repository (e.g., LipidMatch .csv files) and need to audit or report the total number of distinct lipid species and lipid-type…
Use when after performing LOWESS regression on landmark peak RT pairs between a sample and reference, you need to encode the learned RT transformation as a reusable,…
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 raw HPLC column metadata arrays containing Tanaka parameter blocks that will be fed into a featurizer for machine learning on retention times.
Use when you have sampled flux distributions from two or more constraint-based metabolic models representing different biological conditions (e.
Use when when cataloging a suite of related bioinformatics tools or web applications (particularly in domains like metabolomics, microbiology, or systems biology) and you need to…
Use when you have peak intensity vectors from LC/GC-MS experiments with corresponding QC (quality control) sample measurements, and you need to correct for batch…
Use when your metabolomics experiment includes samples acquired across multiple instrument runs, different preparation dates, or distinct sample cohorts.
Use when you have a log2-transformed, standardized peak intensity matrix (rows = metabolite features, columns = samples) with compound annotations mapped to curated pathway…
Use when you have extracted fragmentation patterns from a collection of MS/MS spectra (using mineMS2) and have partitioned spectra into components via GNPS molecular networking…
Use when when you have a loaded metabolite database (e.g., hmdb_compounds.p pickle file) and need to constrain the chemical space to a specific instrumental m/z range (e.
Use when when you have raw or processed direct-infusion MS (DI-MS) or ASAP-MS spectra as mz/intensity pairs and need to rapidly identify salient peaks for species authentication,…
Use when when you have loaded a structure-organism pairs table from a natural products database (e.g., LOTUS) and need to answer questions about the distribution of chemical…
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 you have preprocessed mass spectra (peak-filtered, metadata-cleaned) in supported formats (mzML, mzXML, msp, MGF, JSON) and need to compare all-pairs or many-to-many…
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 when you have raw strain correlation scores (or similar overlap-based metrics) computed across genomic cluster family (GCF) and molecular family (MF) pairs of varying…
Use when you have selected a subset of public tandem MS files from ReDU/MassIVE that have been processed through GNPS spectral library matching, and you need to organize their…
Use when you have vendor-independent centroided mzML files from data-dependent acquisition (ddMS2) HRMS experiments and need to extract a reproducible feature list with mass,…
Use when you have an experimental MS/MS spectrum (m/z and intensity pairs in mzML/mzXML format from DDA or targeted acquisition on Thermo, Waters, or Bruker instruments) and need…
Use when when you need to generate a realistic LC/GC-MS feature table (peak intensity matrix) with controlled, quantifiable condition effects (e.g., differential metabolite…
Use when after peak picking by MS-DIAL and import into R, when the feature table contains m/z values with decimal components that fall within the [4, 8] interval (indicating…
Use when after constructing a kNN graph (via pp.neighbors) on preprocessed, scaled, and PCA-reduced single-cell expression data.
Use when you have experimental MS/MS spectra from nontargeted metabolomics data and need to assign molecular identities or identify structurally related analogs.
Use when you have extracted peaks from multiple LC/HRMS batches (n > 1) with their m/z and RT values, and you need to identify and align peaks representing the same compound…
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 when a new file format specification has multiple language implementations and you need to validate that all implementations correctly interpret the specification.
Use when when you need to aggregate values from multiple records in a JSON input document into a single concatenated string field (e.
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 before executing a bioinformatics pipeline that depends on multiple R packages with strict version constraints (e.g., DaDIA, which requires R ≥4.0, XCMS ≥3.11.4, and…
Use when you have downloaded and extracted a GNPS archive (from METABOLOMICS-SNETS,
Use when you have an untargeted metabolomics feature table (m/z, retention time, p-value from statistical test) but lack comprehensive metabolite identifications or MS/MS…
Use when constructing or enriching a chemical formula database that must capture not just structural similarity (DBEdges) but also biological co-occurrence patterns.
Use when when designing a targeted lipidomics experiment and you have lipid species definitions (including chain composition and adducts) but need to configure precursor–fragment…
Use when you have time-resolved DBDI-MS data (intensity matrix with m/z features as rows and scan timepoints as columns) from direct injection analysis where chromatographic…
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 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 after executing annotateRC to match six or more lipidomics/metabolomics features against ion fragment databases (e.
Use when you have a high-resolution LC-MS/MS experiment with a measured [M+H]+ or [M-H]− ion mass and optionally a parent ion fragmentation spectrum (peak list with m/z and…
Use when when you have an untargeted metabolomics feature table (m/z values, retention times, intensity measurements, and p-values from statistical testing) and want to p — from…
Use when you have MS data in a new format or storage system (e.g., a custom database, HDF5 file, or proprietary raw file) and need to make it accessible to Spectra-based analysis…
Use when after executing the Juicer pipeline on raw Hi-C FASTQ files, to confirm that the pipeline has generated the expected .hic output artifact and that the contact matrix…
Use when when analyzing high-resolution mass spectrometry data from natural-abundance
Use when when applying Scanpy preprocessing functions (e.g., pp.normalize_total, pp.pca) to AnnData objects where the expression matrix X is backed by a dask.array.Array, you need…
Use when you have access to a published study that provides a Jupyter notebook (.ipynb) containing executable code for reproducing simulations, analyses, or figures, and you need…