Use when you have raw line-scan mass spectrometry imaging data from nano-DESI or other line-scan acquisition modes and need to produce a georeferenced 3D pixel array.
Use when you have a binary file (e.g., NV format) with a known fixed-size header block (e.
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 imaging mass spectrometry data from spatial metabolomics experiments and need to reduce the high-dimensional peak space to a ranked set of marker ions for…
Use when you have preprocessed GCF-MF link pairs from paired genomics–metabolomics
Use when when you have a target compound (modified or unmodified) and need to obtain its experimental MS/MS spectrum and metadata to serve as a known reference for ModiFinder…
Use when you have a pre-trained DNN model for retention time prediction and need to adapt it to a new chromatographic method or instrument where you have only 10–20 calibration…
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 suspect XCMS grouping contains misaligned features due to suboptimal parameter settings or insufficient samples.
Use when processing a mass spectrometry dataset (in FragHub JSON format or similar) where duplicate spectral records are suspected or known to exist.
Use when when beginning an untargeted LC-MS analysis and either (1) the dataset characteristics (sample complexity, instrument platform, or polarity) differ from previously…
Use when you are preparing to run a complex multi-tool bioinformatics pipeline (such as HiC-Pro) on a new system or cluster, and need to confirm that all required binaries exist…
Use when after executing a reproducible simulation pipeline (particularly for Over-representation Analysis in metabolomics), compare the newly generated outputs against reference…
Use when after executing an end-to-end structure annotation pipeline (such as BAM) on a validation dataset with known reference annotations.
Use when you have labeled training data (e.g., pqm_development with 500 peaks and 89 samples) and need to select which of multiple classification algorithms (e.g., AdaBoost,…
Use when you have m/z values from spatially-resolved mass spectrometry imaging (e.g., MALDI-MSI, DESI-MSI) and need to assign molecular formulae to thousands of features with…
Use when processing raw IM-MS data (Agilent MassHunter .d or UIMF format) that contains jagged, low-abundance ion peaks or when saturation repair has been applied and the…
Use when when comparing the robustness of multiple pathway ranking methods (e.g., PLAGE, ORA, GSEA) on metabolomics or other omics data, and you need to establish which method is…
Use when training a CNN model from scratch on LCMS peak classification tasks (or similar image-like batched data) where you need to confirm the model reaches target performance…
Use when apply peak-count capping when preprocessing tandem mass spectrometry (MS/MS) spectra for peptide identification or spectral library matching, particularly when working…
Use when you have a tabular file (CSV or Excel) that has been manually or semi-automatically tagged with export tags, and you need to verify tag correctness before running the…
Use when you have MS/MS spectra in .msp format and need to retrieve similar compounds or compute spectral similarities for compound identification.
Use when you need to verify that a GitHub Actions workflow (such as a Build and Publish pipeline) executes successfully on a specific branch (e.g., release branch) and produces a…
Use when releasing a new version of a Python package, validating packaging infrastructure changes, or confirming that distribution channels (PyPI, Bioconda) remain functional…
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 after completing an Environment simulation or replay with scan-level MS2 acquisition control, and evaluation data has been collected in memory.
Use when when you have processed metabolomics LC-MS/MS data organized by batch and sample type (including pooled QC replicates), and you need to quantify whether batch-to-batch…
Use when you have a ProForma 2.0 peptidoform string (e.g., DLTDYLM[Oxidation]K) and need to extract the underlying peptide sequence and map modification positions to enable…
Use when you have tabular data (CSV or Excel) with column headers annotated using MESSES tagging syntax (#<table_name>.id for record identifiers, #.
Use when when you have known metabolite concentrations and their spin-system coupling constants (J-values) and need to generate synthetic ¹H NMR spectra for method validation,…
Use when you have completed Tn5 insertion bias correction on ATAC-seq reads and now need to quantify footprint signal strength (signal depletion around TF-bound sites) across…
Use when you have raw LC-MS/MS data in MRM acquisition mode and need to systematically identify and catalog all precursor m/z and corresponding product m/z values for each…
Use when after sample alignment and peak picking have produced an aligned feature table with m/z and retention time coordinates.
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 a backed AnnData object populated with fragment coordinates (stored in .obsm['fragment_paired'] or .
Use when when analyzing imaging mass spectrometry datasets where you need to reduce high-dimensional peak intensity features while preserving spatial structure, and when automatic…
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 BioTransformer-predicted metabolite structures (in SMILES or InChI format) and need to identify which known compounds in public databases match those structures.
Use when when you have raw molecular structures in SMILES or SDF format that must be prepared as input to a descriptor-based classifier (e.g., BitterPredict).
Use when after loading and preprocessing raw scATAC-seq data into an ArchR project object when you need to compute low-dimensional embeddings for clustering, UMAP/tSNE…
Use when when you need to evaluate how a specific algorithm parameter (such as SearchMolecularFormulas first_hit mode) affects the quantity and quality of molecular formula…
Use when after theoretical spectra have been generated for lipid–adduct combinations with enumerated fragment masses and intensities, and you need to deploy them for downstream…
Use when when you have centroided .mzML LC–MS runs and a target list (compound ID, theoretical m/z, expected RT, polarity) but are uncertain whether your m/z and RT windows are…
Use when you have loaded a feature-by-pixel intensity matrix (HDF5 format following Cardinal::HDF5 layout) from imzML MSI data in positive ion mode and you have identified paired…
Use when you have a set of metabolites or chemical formulas to analyze and want to evaluate how different MS/MS fragmentation strategies (e.g., TopN, exclusion lists, dynamic…
Use when you have generated 1D FID time-domain data and Fourier-transformed frequency-domain 1H NMR spectra, or computed 2D COSY/HSQC correlation matrices, and need to write them…
Use when you have raw untargeted LC/HRMS data (mzXML, mzML, or netCDF format) from population-scale studies (n > 500 samples) and need to extract a comprehensive peaklist with…
Use when you have raw Illumina EPIC or 450k methylation array data (.idat files or beta-valued matrices) and need to perform comprehensive quality assessment, probe correction,…
Use when you have sparse, single-cell or bulk ATAC/DNAse-seq data from multiple cell types or conditions (e.g., GM vs H1 cell lines), pre-filtered and GC-bias-corrected, with…
Use when after simulating and convolving individual metabolite multiplets with realistic lineshapes (Lorentzian or Gaussian) and combining them into a single time-domain FID array.
Use when you have raw or processed arrival-time data from a TWIM-MS instrument and need to convert it to CCS values for comparison across experiments or biomolecular classes.
Use when you have a genome annotation GTF file and need to identify all transcript-level alternative splicing events (exon skipping, intron retention, alternative splice sites,…
Use when when you have deposited a collection of JSON project documents in a platform and need to verify that all conform to the published schema before public release or — from…
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 a metabolite feature has been assigned a top-rank lipid annotation (e.g., LPC(14:0)) but you need to assess whether related lipid species containing the same fatty…
Use when when predicting one data modality (e.g., metabolite abundances) from another (e.g., microbiome composition) and you need to distinguish genuine microbe–metabolite…
Use when you have a trained NeatMS neural network model (.h5 format) and need to assess its classification performance at a specific decision threshold (e.g., 0.01) to de — from…
Use when you need to serialize heterogeneous data (e.g., index integers and file offsets of different byte widths) into a compact binary format, or parse a binary file format…
Use when you have sequential QCpool (pooled quality control) samples analyzed with Sciex Multiquant (≥v3.0.
Use when when you have mass spectrometry data organized in a Pandas DataFrame with m/z values, retention time (RT), and intensity measurements, and you want to visualize the joint…