Use when when you have a USI string (e.g., mzspec:GNPS:TASK-d93bdbb5cdda40e48975e6e18a45c3ce-... — from HolobiomicsLab/asb-skill-collections
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 a normalized metabolite abundance matrix with sample metadata assigning each sample to one of three or more distinct biological classes (e.
Use when you have a MetaboLights dataset identifier (e.g., MTBLS1124) and need to download a specific mzML file (e.g., QC07.mzML) from the public repository for visualization,…
Use when you have CE-MS test files archived in the msdata Bioconductor package and need to load them into an in-memory or on-disk R representation to extract ion…
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 you have a list of identified or suspected chemical compound names (e.g., from GC-MS Match.
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 raw or extracted peak feature table (CSV or tabular format) containing mass-to-charge ratios, retention times, and intensity values across multiple samples…
Use when when you have log-transformed metabolite abundance data from multiple batches (e.
Use when when developing or extending mass spectrometry data processing workflows (e.
Use when after m/z grouping and pairwise alignment detection when you have a metabCombiner object containing candidate feature pair alignments and need to select a subset of…
Use when you have downloaded LC-MS spectral peak data (DOI 10.25345/C5FD2F or equivalent) and need to build a supervised deep neural network classifier to distinguish peak classes…
Use when you have independently generated or received both scATAC-seq peak count matrices and scRNA-seq gene expression matrices from the same set of cells (multiome experiment),…
Use when when building Word2Vec or embedding-based spectral similarity models where you need to capture fragmentation patterns beyond individual peak positions.
Use when after running a ViMMS simulation loop with a fragmentation controller (e.
Use when when processing raw CE-MS data and need to establish a baseline migration time scale before transforming to effective mobility.
Use when after identifying statistically significant features and assigning them to structural clusters (isotopologue groups, adduct groups, cross-assay links) and correlation…
Use when you have executed batch searches of MS/MS spectra against multiple domain-specific MASST indices and need to synthesize results across domains (e.
Use when when you need to capture a snapshot of a research software project's health metrics from multiple CI/CD and repository services (Travis CI, Landscape.
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 need to reverse-engineer or document the architecture of a multi-component research software system where design information is embedded in repository structure,…
Use when you have preprocessed MS/MS spectral data (normalized peak intensities and m/z values) in memory or on disk, a trained CNN model checkpoint available, and you ne — from…
Use when after identifying statistically significant LC-MS features (e.g. via MB-VIP permutation testing) when you need to consolidate redundant measurements of the same…
Use when preprocessing open mass spectrometry libraries (OMSLs) or aggregated spectral datasets where structural identifiers are inconsistently populated.
Use when you have raw GC-MS output in CSV format (with Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, and File.Name columns) and need to systematically…
Use when when analyzing DNA methylation data from bisulfite sequencing (RRBS, target-capture, or whole-genome) and the dataset is too large to fit comfortably in memory, or when…
Use when you have aligned single-cell ATAC-seq data as BAM files or fragment files (TSV format with genomic coordinates) and need to prepare it for spectral embedding, clustering,…
Use when you have a spectral library with structural ground truth (InChIKey or SMILES annotations for ≥50% of spectra) and want to benchmark whether a new or existing spectral…
Use when you have MS2 spectra data (MGF/mzML format) and aligned feature tables, and your analysis goal is to compare samples that may have poor MS1 feature overlap, strong…
Use when you have LC-MS/MS data preprocessed with MZmine2 into an MGF file (containing MS1 and MS2 spectra) and a feature table (peak areas per sample), and you want to relate MS1…
Use when after preprocessing a set of aligned 2D-TIC (two-dimensional Total Intensity Chromatogram) matrices from GCxGC-MS experiments—when you have multiple samples across…
Use when you have measured IM-MS lipidomics data spiked with U13C labeled internal standards and need to assess whether CCS bias remains within acceptable limits for each lipid…
Use when you have a query mass spectrum (or a metabolite reference spectrum from public data) and need to search it against a large-scale spectral repository (≥billions of…
Use when after frequency-based denoising has been applied to individual replicate spectra within each feature (via generate_denoised_spectra), you have a collection of denoised…
Use when after feature detection has produced a feature table with zero and missing values (sparse abundance matrix) but before multivariate statistical analysis or annotation.
Use when you have candidate library matches from MS2Deepscore ranking (top 2000 spectra per query) with InChIKey annotations, and need to quantify structural similarity between…
Use when when you have deposited a collection of JSON project documents in a platform or repository and need to verify that all conform to a published JSON Schema specifi — from…
Use when preparing raw ion image data from mass spectrometry imaging for deep learning-based representation learning.
Use when after completing Part 4 (Identification of ISF Features) in the ISFrag workflow, when you have an analysis results object containing identified ISF features and need to…
Use when when processing aligned LC-MS data across multiple samples where the computational bottleneck is repeated peak-detection algorithm calls (one per sample per m/z value).
Use when parsing, standardizing, or filtering MS spectra from mixed or heterogeneous databases where adduct assignment may be manually entered, auto-inferred, or missing.
Use when you have a compressed file format (e.g., igzip) with a custom binary header structure that encodes metadata (index-to-offset mappings) in a fixed layout, and you need to…
Use when a spatial metabolomics dataset contains semicolon-delimited isomer name annotations (e.g., 'all_IsomerNames' column in SpaMTP Seurat objects) and you need to collapse…
Use when your research involves searching MS/MS spectra against multiple curated taxonomic or domain-specific databases (microbial, plant, tissue, microbiome, or food origin) and…
Use when when building a comprehensive chemical knowledge base for mass spectrometry formula assignment, particularly when you need to link chemical formulae across heterogeneous…
Use when you have executed a structure annotation pipeline (like BAM) on a validation dataset for which ground-truth molecular structure annotations exist, and you need to assess…
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 a set of gallery or example scripts that must run consistently across multiple backend implementations (e.g., matplotlib, Bokeh, Plotly), and you need to verify…
Use when you are preparing to reuse public tandem MS data from MassIVE via ReDU and need to partition files by sample metadata (e.g., organism, tissue type, extraction method,…
Use when when preparing to execute the Nextflow4MS-DIAL workflow on raw LC-HRMS metabolomics data (.mzML or .
Use when when building a comprehensive lipid fragment ion library covering all chain composition and positional isomer variants (e.g., 168.6 million entries).
Use when you have a pre-generated .hic contact map file (from Juicer pipeline or external source) and need to systematically call chromatin loops, detect topologically associating…
Use when when you need to understand how a complex feature or architectural pattern was implemented in a codebase, particularly when the current README or documentation does not…
Use when you have raw SMILES strings from a chemical database (e.g., CCSBase, METLIN, or custom sources) and need to feed them into a graph neural network model.
Use when you have a trained deep learning model and want to quantify prediction uncertainty for each input pair or decision point.
Use when you have generated hypothetical links (e.g., GCF–MF pairs) and computed multiple independent scoring functions on them (e.g., strain co-occurrence, IOKR structural…
Use when after quantifying ion images in LipidQMap and before exporting to HDF5 format, when you need to organize per-feature metadata (lipid ID, class, adduct, m/z, internal…
Use when you have loaded normalized methylation data from EPIC or 450k arrays and need to identify differentially methylated blocks rather than individual CpG sites or DMRs.
Use when after extracting tabular data into intermediate JSON form or after applying matrix conversion directives (e.