Use when designing multi-batch LC/GC-MS experiments where samples belong to multiple groups or conditions and you need to ensure that each injection plate receives a balanced…
Use when you have a pair of MS/MS spectra—one from a known compound and one from a structurally modified variant of that compound—and you need to identify which atoms in — from…
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 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 you have paired mass-spectrometry spectral data (m/z and intensity arrays) with known molecular fingerprints or InChIKeys, and need to train a supervised deep learning…
Use when apply CLR transformation when working with microbiome or metabolomic relative abundance tables that will be input to multivariate regression or neural network models.
Use when you have normalized peak intensities using MetaboDirect's data preprocessing step and are preparing to perform PERMANOVA or NMDS ordination on a bacterium-phage or…
Use when you have a methylDiff object containing differentially methylated bases or regions from bisulfite sequencing, gene annotation in BED or similar format (RefSeq, Ensembl),…
Use when after XCMS feature detection, grouping, retention time correction, and missing value filling have produced an aligned feature matrix, when you need to group features…
Use when you have Thermo Fisher Scientific .raw files from an LC-MS experiment and need to extract spectral features (base-peak m/z, intensity, scan-level properties) indexed by…
Use when when you have mass-to-charge (m/z) values from mass spectrometry imaging or other MS experiments and need to assign molecular formulae with high precision, especially in…
Use when after sample alignment in untargeted LC-MS workflows, when the aligned feature table contains missing (NA or zero) intensity entries for features that are detected in…
Use when you have a ranked list of library candidates (top 2000 by MS2Deepscore)
Use when you have high-resolution tandem MS spectra (in mzML, mzXML, or MGF format) that need to be clustered or searched at scale (millions of spectra).
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 after training a GNN-RT model on preprocessed molecular graph data (from Train.py) or after applying transfer learning to an in-house dataset (from Transferlearning.
Use when apply TMM normalization when you have raw RNA-seq read counts from multiple samples and suspect differences in library composition (e.g., one sample over-represents a…
Use when you have raw Hi-C FASTQ files from a kilobase-resolution Hi-C experiment and need to produce a processed Hi-C contact map (.hic file) for visualization, loop calling, or…
Use when you are designing a new tool for FT-ICR MS analysis (or similar high-resolution mass spectrometry domain) and need to understand which analytical and visualization…
Use when you have retrieved and deduplicated chemical formulae and metadata from multiple heterogeneous sources (HMDB, ChEMBL, PubChem) and extracted both structural relationships…
Use when you have implemented both CPU and GPU versions of a spectral search algorithm (e.g., approximate nearest neighbor indexing with cascade filtering) and need to validate…
Use when you have merged methylation call data across multiple biological replicates (samples per group ≥2) with base-pair-level coverage information, and you need to identify…
Use when you have normalized gene expression data (log-transformed, quantile-normalized) from a time-course or case-control experiment, a ranked gene statistic (e.g., mean…
Use when when you have raw LC-MS all-ion fragmentation (AIF) chromatograms in centroid mode and need to prepare them for metabolite annotation using fragment ion matching.
Use when when you have RNA-seq count matrices (from HTSeq, featureCounts, Salmon, kallisto, or RSEM quantification) and need to test for differential expression between two or…
Use when when you have unknown MS/MS spectra with observed precursor m/z values and want to infer the molecular formula and adduct type (e.g., [M+H]+, [M+Na]+, [M+K]+) in a de…
Use when ingesting or validating project JSON documents against a schema (such as app/public/schema.json in the Pairing Omics Data Platform) that designates certain fields as URL…
Use when your input is a spatial dataset (AnnData object with coordinate metadata) paired with a large tissue image, and you need to extract spatial features (via…
Use when you have a collection of records in a standardized format (e.g., MassBank plain-text or structured records) that must be validated before commit or publication.
Use when you have a query mass spectrum matched to multiple candidate metabolites (by accurate mass, database lookup, or spectral similarity), and you possess or can train a DNN…
Use when you have a pretrained TCN spectrum encoder from formula prediction and need to train a rescoring model that ranks formula candidates by confidence.
Use when when running metabologenomic RiPP detection pipelines (MetaMiner) on the same genomic dataset but with different input sequence formats (e.g., contigs.fasta vs.
Use when you have paired genomic (BGCs clustered into GCFs via BiG-SCAPE) and metabolomic data (MS2 spectra grouped into MFs), with strain/sample co-occurrence patterns and…
Use when when you need to generate 2D metabolomic NMR spectra (COSY for homonuclear or HSQC/HMQC for heteronuclear correlations) from parsed metabolite concentration and…
Use when you have a metabolite intensity matrix (rows=metabolites or peaks, columns=samples) paired with metabolite-to-pathway or metabolite-to-feature-group annotations, and you…
Use when you have raw or unprocessed MS/MS spectral data in standard metabolomics formats (MGF, mzML, mzXML, msp, or JSON) and need to import them into a Python-based workflow for…
Use when you have a normalized matrix of feature attribution scores (microbes × metabolites) derived from a trained neural network, and you want to partition both microbes and…
Use when you have generated a peak table or feature list output file from an external peak-picking tool (MZmine, XCMS, MS-DIAL, or Compound Discoverer) in its native export format…
Use when after mass track extraction from individual LC-MS samples, when you need to align mass tracks across a cohort to produce a unified feature matrix.
Use when after running XCMS-based alignment on LC-MS datasets with hundreds of samples or data acquisition periods longer than a week, when the assumption that all m/z bins in the…
Use when you have a tab-delimited feature table (m/z, retention time, intensities) from LC-MS preprocessing and need to group related ions (isotopologues, adducts, in-source…
Use when when preparing heterogeneous column-metadata inputs for a graph transformer model that operates on molecular graphs.
Use when you have raw peak tables exported from a tandem mass spectrometry preprocessing tool (e.g. Progenesis, MS-DIAL, or Bruker Metaboscape) and need to integrate them with…
Use when when you have computed Spec2Vec similarity scores (typically cosine similarity in [0, 1] range) between discovered Mass2Motifs and a spectral library, and need to decide…
Use when you have raw or minimally processed single-cell RNA-seq expression data loaded into an AnnData object (dense, sparse, or Dask-backed array as X), and you need to apply…
Use when you have mass spectrometry feature data stored in HDF5 format (.h5 files) and need to load specific dimensional columns (m/z, drift time, retention time, intensity) for…
Use when you have identified a published method (e.g., MIST-CF for chemical formula ranking from mass spectra) whose source code and trained weights are available in a public…
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 when you have real LC-MS/MS data (mzML format) from an untargeted metabolomics experiment and want to test how variations in TopN DDA parameters affect which precursor…
Use when when you have received or cloned a CCS reference library (such as the DTCCSN2 library for U13C labeled lipids) bundled with lipidomics software and need to verify its…
Use when after running Enrichment() on a configured EnrichParam object (via KEGG_Enrich_PlotPanel or similar), when you have a full enrichment result table and need to reduce it…
Use when when you have preprocessed MALDI-MSI data (in msimat format) and want to determine whether abundant peaks are actually molecular adducts of simpler parent ions rather…
Use when you have acquired LC-MS peak tables from both unlabeled (12C) and isotope-labeled (13C) samples from a stable isotope tracing experiment, paired with sample metadata…
Use when you have LC-MS/MS spectral data (in MGF, mzXML, mzML, or mzData format) and corresponding genomic sequence data (raw FASTA nucleotide sequences or genome mining tool…
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 transcript-level quantification (salmon, Sailfish, or kallisto output) summarized to gene level by tximport, and you observe or suspect differential isoform…
Use when after converting or filtering objects (e.g., transformation products to suspect lists, feature groups through componentization) and before passing them to downstream…
Use when you have modified the Scanpy codebase (e.g., added a feature or bugfix) and need to confirm that all unit and integration tests pass before submitting a pull request, or…
Use when you have paired cdf files (raw mass spectrometry imaging data) and Matlab workspace (.mat) files for the same root sample, and you need to reproduce published linear-axis…
Use when when training a regularized deep neural network for molecular property regression (e.g., retention time prediction on the METLIN SMRT dataset with 80,038+ samples), use…