Use when after mass tracks have been aligned across all samples (either via pairwise alignment for ≤10 samples or nearest-neighbor clustering for larger cohorts), and you need to…
Use when after running macs3 callpeak with the -f BEDPE flag on paired-end ChIP-Seq data (e.g., CTCF_PE_ChIP_chr22_50k.bedpe.
Use when when you have a mass spectrometry data file (such as mzPeak) that has been read by two or more independent implementations (e.g., Rust, Python/pyarrow, R/arrow) and need…
Use when when you have a preprocessed bag-of-fragments corpus from tandem mass spectrometry spectra and need to train an MS2LDA model to discover Mass2Motifs.
Use when when processing multiple centroided mzML LC-MS files from the same study and you need to identify which mass tracks represent the same metabolite across samples.
Use when you have filtered ATAC-seq peak counts, matched motifs to those peaks, and want to measure which transcription factor motifs show elevated or reduced accessibility…
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 after feature detection when you have a feature table with m/z, retention time, and intensity columns, and you need to group features into empirical compounds (putative…
Use when you have loaded raw Agilent Unknowns Analysis CSV output with required columns (Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when when setting up a new conda environment for a Python-based bioinformatics pipeline and you need to confirm that all declared dependencies (e.g., pysam >=0.15.4, bx-python…
Use when after constructing a network graph where nodes represent Mass2Motifs (or spectra) and edges encode pairwise spectral similarity scores, and you need to export the network…
Use when when adopting a mass spectrometry data processing tool (e.g., LipidMatch) and needing to verify whether your specific instrument platform (vendor + model) and acquisition…
Use when you have Sciex Multiquant text export files from one or more metabolomics or lipidomics analytical sequences and need to identify and locate QCpool (pooled quality…
Use when you have raw LC-MS/MS spectral data in vendor formats or unvalidated .mgf files before feeding them into the specXplore importing pipeline.
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 a pretrained model with documented performance on a bounded input domain (e.g., molecules ≤19 heavy atoms, sequences <1000 bp) and you need to establish whether…
Use when you have one or more vendor mass spectrometry raw files (Thermo .raw, Agilent .d, Sciex .wiff2, or other MSConvert-supported formats) that must be converted to Aird…
Use when you have generated a feature table via mzrtsim() with simulated LC/GC-MS abundances, condition assignments, and batch labels, and you need to pass it to Bioconductor…
Use when you have raw mass spectrometry files in standard formats (mzML, mzXML, msp, MGF, JSON) and need to extract precursor m/z values, fragment peaks, neutral losses, retention…
Use when when you have a real mzML file from an untargeted metabolomics LC-MS/MS experiment and need to extract the chemical features it contains—either to simulate a…
Use when when you have a training set of MS2 spectra with known chemical structures (e.
Use when you have ATAC-seq BAM files and a set of genomic coordinates (e.g., transcription factor motif sites, peak regions) and need to quantify the spatial distribution of Tn5…
Use when when you have a pre-computed hierarchical dendrogram from structural clustering (e.g., of LC-MS features based on m/z and retention time) and want to compare or validate…
Use when when you have aligned ChIP-Seq reads (single-end BED or paired-end BEDPE format) and need to identify enriched genomic regions by comparing ChIP signal against control…
Use when you have LC-MS peak tables from parallel unlabeled and labeled (isotope-traced) sample cohorts, sample metadata defining groups and conditions, and you seek to identify…
Use when you have raw MS2 spectra files (mzML, mgf, msp, mzxml) that may contain multiple MS2 spectra per feature and require reduction or standardization before library matching.
Use when after obtaining 512-dimensional representation vectors from the Encoder module, when you need to compress these vectors for visualization, clustering, or downstream…
Use when you are performing dimensionality reduction on a sparse single-cell count matrix (in CSR format) and need to compute pairwise cell similarities before spectral…
Use when when processing CE-MS test files and you need to identify and extract the migration time of the EOF marker (e.g., Paracetamol) to normalize compound migration times…
Use when immediately after loading raw single-cell gene expression count matrices (AnnData objects) and before identifying highly variable genes or performing dimensionality…
Use when when you have .msp mass spectrometry metadata containing chemical identifiers (e.g., compound names or SMILES strings) and need to compute derived chemical properties…
Use when when you have two independent predictions of categorical outcomes (up/down/no-change variation signs) across multiple sample pairs and need to measure agreement beyond…
Use when you have acquired raw MS/MS spectra (in MGF or mzML format) from a mass spectrometry instrument or public repository (e.g., MassIVE, MetaboLights, GNPS) that will be used…
Use when you need to evaluate whether a newly released or candidate library (e.g., spectrum_utils v0.4.
Use when after generating consensus spectra with fragment recurrence frequencies, when you have replicate MS/MS spectra for features and need to choose a single frequency cutoff…
Use when you have millions of MS/MS spectra in mzML, mzXML, or MGF format and need to identify similar spectra for clustering, but exhaustive pairwise cosine-similarity…
Use when you have tabular metabolomics data (tab-delimited or Sciex OS format) and need to apply a specialized R package's analysis pipeline—such as mzQuality—that requires…
Use when analyzing raw 2D MS data (m/z vs. retention time maps) where conventional peak picking introduces unacceptable error rates, particularly in untargeted metabolomics or…
Use when when comparing transcript quantification outputs (NumReads counts, abundance estimates) from two mapper implementations (e.
Use when you have a batch of mass spectra records in .msp format that lack standardized metadata fields (SMILES, InChI, CAS numbers, molecular formula, IUPAC names) and need to…
Use when after biomolecular class labels have been assigned to features in a TWIM-MS dataset and you have raw ion mobility arrival time measurements.
Use when after generating a frequency count table (e.g., from count_fold_changes
Use when when you have an aligned GCIMS dataset and need to configure the findPeaks function with CWT algorithm to detect peaks across retention time and drift time dimensions.
Use when setting up a LipidMatch analysis run and you need to select among three mutually-exclusive analysis modes (PFAS, Lipid, or Tween-positive detection).
Use when working with GCIMS datasets where retention time spans a wide range (e.g., 0–1500 s) but your analytes of interest are confined to a narrower window (e.g., 0–1100 s).
Use when your metabolomics analysis pipeline requires CCS value prediction for ion-mobility mass spectrometry data, you have access to a curated training set of known metabolites…
Use when you have SMILES-encoded molecular structures and need to model their behavior under electrospray ionization (ESI) or other ionization methods in mass spectrometry.
Use when you are selecting a pathway enrichment method for metabolomics peak data and need to assess which method will remain stable when your data contains noise, dropout, or…
Use when when you have CE-MS data with migration times that vary between runs due to electroosmotic flow drift, but you possess a reliable internal standard with a known effective…
Use when you have raw MS/MS spectral data in standard mass spectrometry formats and need to prepare it for unsupervised substructure discovery via topic modeling.
Use when you have completed the MS2LDA LDA modeling phase and possess motifset.json or motifset_optimized.json files containing inferred Mass2Motifs.
Use when when you have raw GC-MS output (CSV with columns: Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
Use when you have extracted retention times from top MS1 features across an LC-MS run and need a single, comparable metric to evaluate how effectively a gradient spreads compounds…
Use when when building a file I/O abstraction layer that must support multiple serialization formats (e.g., uncompressed mzML, gzip-compressed mzML, indexed gzip mzML, or…
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 you have a pre-trained DNN RT predictor (e.g., trained on METLIN SMRT with 80,038 experimental RTs) and need to adapt it to predict retention times in a new or external…
Use when when you have generated separate MemoMatrix objects from independent sample sets (e.g., sample set A and sample set B) and need to align and combine their MS2 fingerprint…
Use when you have fit a linear model to normalized gene expression data (microarray intensities or RNA-seq counts) and need to test for differential expression across experimental…
Use when when you have access to a research repository or README documenting a machine learning implementation (e.g., Keras/TensorFlow-based deep learning model) and need to…
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…