Use when when you have high-resolution LC-MS/MS data for an unknown metabolite or small molecule, have computed or measured the molecular ion mass and fragmentation spectrum, and…
Use when you have peak-picked MS/MS data (e.g., from MZmine, XCMS, MS-DIAL, or Compound Discoverer) and need to identify lipid species present in your sample.
Use when a mature scientific package (e.g., Mummichog 3) is being migrated to a new GitHub organization that enforces standardized project structure, and the current setup.py,…
Use when after loading centroided .mzML LC-MS data and defining a target list (compound ID, name, m/z, RT, polarity) when you need to: (1) automatically locate and integrate peaks…
Use when you have raw Hi-C FASTQ files from a high-throughput chromatin conformation capture experiment and need to generate a normalized contact matrix (.hic file) for downstream…
Use when when you have paired augmented ion images processed through ResNet18 encoders producing 512-dimensional representation vectors, and you need to learn meaningful…
Use when you have claims in a paper or tool documentation that one peak picking method outperforms others (e.g., 'IDSL.IPA outperforms MZmine 2 and xcms'), but the specific…
Use when you have raw LC-MS spectral peak data (in the format provided by DOI 10.25345/C5FD2F) and need to build a classifier that can distinguish valid peaks from false positives…
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 you have acquired a versioned QC workflow definition file (YAML or JSON) from a metabolomics QC system release (e.g., v1.0.
Use when after computing deviations for both motif and kmer annotations on the same chromVAR dataset, when you need to determine whether kmers and motifs are redundant predictors…
Use when your R-based Spectra analysis workflow requires a specific mass spectrometry algorithm (e.g., CosineGreedy similarity scoring, spectral normalization, or advanced…
Use when you have a generic constraint-based metabolic model (SBML format) and cross-sectional omics data (RNA-seq, intracellular metabolomics, YSI or bioanalyzer extracellular…
Use when after executing multidimensional smoothing, spike removal, or saturation repair on raw TOF-MS or IM-MS data (.d format from Agilent MassHunter) to confirm that signal…
Use when after generating a tile matrix or feature count matrix from single-cell ATAC-seq, RNA-seq, Hi-C, or methylation data, before clustering or UMAP visualization, when you…
Use when when you have a trained multitask model that accepts multiple input modalities (e.g., 1D NMR spectra in different nuclei or complementary analytical techniques) and you…
Use when you have a normalized count matrix (from Salmon or similar quantification
Use when you have a backed AnnData object containing processed fragment data (stored in .obsm['fragment_paired'] or .
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 you have an unknown mass spectrum (or a representative metabolite spectrum from public data) and need to identify it by comparing it against a large reference…
Use when when you have raw profile LC-MS data in .mzML format and need to prepare regions of interest (ROI) as input for a CNN-Transformer peak detection network.
Use when you need to verify that a GitHub Actions workflow (such as 'dev_build_release.
Use when you have raw LC-MS data in vendor or mzML format and need to systematically discover and extract all detectable metabolite features across the full retention time range,…
Use when after running an end-to-end annotation workflow (matching, clustering, filtering, and prioritization) on untargeted LC-MS peak tables, when you have access to a curated…
Use when after running RAMClustR clustering on XCMS-detected LC-MS features in positive ionization mode, when you need to assign molecular weights to compound clusters and want to…
Use when you have intracellular metabolomics concentration measurements across multiple cell lines or conditions, a stoichiometric metabolic network model with reaction-metabolite…
Use when after running PERMANOVA on distance matrices derived from FT-ICR MS metabolite peak intensities or other high-dimensional compositional data, when p-values indicate…
Use when when you have 512-dimensional (or other fixed-size) representation vectors output from paired encoders processing augmented versions of the same input (e.
Use when when you have a collection of molecular structures (as InChI strings, SMILES, or RDKit Mol objects) and need to feed them into a pretrained or transfer-learning neural…
Use when when a software project has reached a stable milestone (v-tagged commit) and you need to produce official distribution artifacts with verified version metadata,…
Use when when you have a GTF genome annotation and need to catalog all transcript isoforms and local alternative splicing event variants (exon skipping, intron retention,…
Use when after executing a spatial statistics function (e.g., squidpy.gr.sepal) on a spatial transcriptomics dataset in AnnData format, and before using the computed rankings or…
Use when when implementing new scoring components (inchikey score, neighbourhood
Use when you have statistically significant LC-MS features (e.g., filtered by p-value < 0.01) from multi-assay metabolomics datasets and need to group features that represent the…
Use when when preparing mass tracks for retention-time (RT) alignment across multiple LC-MS samples.
Use when you have raw GC-MS output in CSV format (with columns: Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when when you have access to the source code of a chemo-informatics tool (e.
Use when immediately after calling squidpy.gr.spatial_neighbors() or similar spatial graph construction methods on an AnnData object.
Use when you have a compiled EI or MS2 library object (from read_lib or c() combination of multiple sources) and a local NIST library installation with accessible ri.dat and…
Use when you have reproduced a release artifact locally (e.g., via Semantic Release or a build tool) and need to verify it matches the official GitHub release record.
Use when after statistical analysis (e.g., MB-PLS with permutation testing) has identified a subset of significant LC-MS features (p < 0.05 or similar threshold) that require…
Use when you have ion mobility-mass spectrometry lipidomics data from samples spiked with U¹³C-labeled lipid internal standards (fully labeled yeast extract) and want to assess…
Use when you have raw GC-MS output exported as CSV (containing columns: Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when when processing in-silico or experimental MS spectra records from databases with incomplete metadata, specifically when the adduct field is null or absent but the ionmode…
Use when you have raw .msp spectral library files (e.g., from MassBank or custom sources) and need to convert them into a structured CSV library format for use in metabolite…
Use when you have a mature Python package (e.g., Mummichog 2.x) that needs to be relocated to a new GitHub organization (e.
Use when you have transcript-level quantification files (quant.sf, kallisto abundance.h5, or RSEM output) from one or more RNA-seq samples and need to construct a count matrix for…
Use when you have untargeted LC-MS metabolomics data preprocessed with XCMS and need to filter out low-quality peak integrations that could introduce false positives or noise into…
Use when you have two augmented versions of the same ion image (from mass spectrometry imaging data) and need to extract learnable 512-dimensional feature representations using a…
Use when after retrieving a JSON or tabular response from a web service endpoint (such as CANOPUS), validate the result before parsing or integrating it into your analysis…
Use when you have aligned ATAC-seq BAM files, corrected Tn5 insertion bias and computed footprint scores (via TOBIAS ATACorrect and ScoreBigwig), a motif database in JASPAR or…
Use when when you have trained multi-layer perceptron neural network models on paired microbiome-metabolome data (from ≥10-fold cross-validation iterations) and need to identify…
Use when apply TIC normalization when you have raw, unprocessed mass spectrometry data (Cardinal objects or imaging matrices with 10,000+ m/z features and 1,000+ spectra) where…
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 when you have deposited mass spectrometry imaging data in NetCDF (CDF) format paired with MATLAB workspace files (.
Use when when you need to verify that a Java project's automated build pipeline (GitHub Actions workflow) executes without errors and generates distributable artifacts (e.g., .deb…
Use when you have a pre-trained GNN model checkpoint, a test dataset with molecular representations (SMILES, 3D coordinates, adducts) and ground-truth labels, and need to quantify…
Use when you have untargeted metabolomics MS/MS spectra from multiple features and need to identify which features belong to the same molecular family or are related by…
Use when when you have raw GCxGC-MS data imported from NetCDF into a 2D-TIC chromatogram object and need to remove chemical and instrumental noise (column bleeding, baseline…
Use when you have completed Hi-C map generation (producing .hic files from aligned reads) and need to detect and annotate topological features such as chromatin loops,…