HolobiomicsLab
- 11k skills
- 0 followers
- last month last updated
- ▌ Lcms Feature Detection And Quantification 3 · holobiomicslabUse when you have raw LC-MS data (mzML or equivalent format) from a metabolomics experiment and need to extract a reproducible, quantified feature table with intensity measurements before conducting metabolite identification or statistical analysis.
- ▌ Mass Spec Tolerance Parameter Application 2 · holobiomicslabUse when when you have a feature table from Orbitrap LC-MS containing m/z, retention time, and intensity columns, and you need to group individual mass features into putative metabolites that represent the same chemical entity across different ionization states and isotopic compositions.
- ▌ Mass Spectrometry Chromatogram Generation 2 · holobiomicslabUse when after MS2 annotation and sample alignment have been completed in JPA, when you need to visualize ion chromatograms for quality control, validate feature identities, or export chromatographic evidence for specific metabolic features across multiple samples.
- ▌ Metabolite Feature Annotation Aggregation 3 · holobiomicslabUse when after selecting statistically significant features from multi-assay LC-MS metabolomics datasets (e.g., via MB-VIP and permutation testing with p < 0.01).
- ▌ Metabolomics Peak Detection Configuration 4 · holobiomicslabUse when when preparing to process raw LC-HRMS metabolomics data (.mzML or .abf files) with MS-DIAL within a Nextflow pipeline, before executing peak detection and chromatogram alignment.
- ▌ Microbiome Metabolome Prediction Modeling 4 · holobiomicslabUse when you have paired microbiome (16S rRNA, metagenomic) and metabolomic (LC-MS, GC-MS) abundance tables from the same biosamples, and you want to predict which metabolites are recoverable from microbial composition alone and identify groups of microbes and metabolites with correlated.
- ▌ Molecular Graph Neural Network Adaptation 2 · holobiomicslabUse when you have an in-house collection of liquid chromatography spectra and retention time measurements for small molecules, and you want to improve structural identification accuracy by predicting retention times.
- ▌ Molecular Structure Prediction Evaluation 3 · holobiomicslabUse when you have trained a multitask NMR-to-structure model and need to quantify its predictive accuracy on held-out test molecules.
- ▌ Molecular Structure Prediction Validation 2 · holobiomicslabUse when when you have executed the MultiModalSpectralTransformer architecture on a set of multi-modal spectroscopic inputs (NMR, HSQC, COSY, IR) and obtained predicted molecular structures, and you need to assess prediction accuracy and structural correctness against ground-truth or reference.
- ▌ Software Feature Inventory And Comparison 4 · holobiomicslabUse when you need to assess whether a newly developed FT-ICR MS pipeline (e.
- ▌ Stable Isotope Probing Abundance Modeling 2 · holobiomicslabUse when you have a high-resolution mass spectrum (FT scan) containing a peptide precursor at known charge state with known or suspected stable isotope labeling (e.
- ▌ Structural Similarity Scoring Metabolites 3 · holobiomicslabUse when when you have paired MS/MS spectra from unknown metabolites and a reference database of known metabolites, and you want to rank candidate structures for unknown compounds by their predicted structural similarity rather than exact spectral matching.
- ▌ Ms Vendor Documentation Extraction 3 · holobiomicslabUse when you need to determine the complete set of validated instrument/vendor and acquisition mode combinations for a mass spectrometry analysis tool, when assessing whether your specific instrument platform (vendor, model, acquisition method) is supported before committing to a workflow, or when.
- ▌ File Format Conversion Validation 2 · holobiomicslabUse when when you have raw mzML or mzXML mass spectrometry data files that need to be archived or transmitted with minimal storage footprint, and you must verify that the decompressed output exactly reproduces the original input at the byte level.
- ▌ Model Generalizability Evaluation 2 · holobiomicslabUse when you have a pre-trained or newly retrained graph neural network for collision cross section prediction and need to measure whether its performance generalizes across different molecular datasets (e.g., training on METLIN but evaluating on CCSBase).
- ▌ Quality Control Metric Evaluation 3 · holobiomicslabUse 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 class-adduct combination.
- ▌ Breath Volatile Peak Classification 2 · holobiomicslabUse when after feature extraction and alignment when you have a numerical feature table (CSV or dataframe) with intensity values across retention time or m/z dimensions, and you need to identify and rank peaks by signal quality and prominence rather than relying on all extracted features equally.
- ▌ Chromatographic Peak Classification 2 · holobiomicslabUse when you have (1) a benchmark dataset of reference peaks with validated m/z, retention time boundaries, and isotopologue assignments, and (2) NPP output feature tables (unaligned and aligned) from tools like XCMS, MZmine 2, or MS-DIAL that you wish to evaluate.
- ▌ Functional Trait Diversity Analysis 3 · holobiomicslabUse when when you have abundance-normalized FT-ICR MS peak data with assigned molecular formulas and need to distinguish between richness (total number of distinct metabolites) and functional diversity (diversity in metabolic potential).
- ▌ Interactive Plot Backend Evaluation 2 · holobiomicslabUse when you have mass spectrometry data (chromatograms, spectra, peak maps, mobilograms) that you want to visualize interactively using pyOpenMS-viz, and you need to select between bokeh and plotly backends based on execution time and feature parity.
- ▌ Metabolite Abundance Stratification 3 · holobiomicslabUse when you have a peak-abundance matrix from FT-ICR MS (peaks as rows, samples as columns with raw peak intensities) and need to compute abundance-based diversity indices or functional diversity metrics that are sensitive to relative vs. absolute peak heights.
- ▌ Pubchem Compound Database Retrieval 2 · holobiomicslabUse when you need to supply candidate metabolite structures for mass spectrometry annotation when working within an integrative metabolomics data analysis workflow (such as MAGMa).
- ▌ Retention Time Alignment Evaluation 2 · holobiomicslabUse when you have run an NPP tool (XCMS, MZmine 2, etc.) on mzML files and need to assess whether the alignment stage preserved peak detection fidelity and isotopologue abundance ratios.
- ▌ Retention Time Intensity Extraction 2 · holobiomicslabUse when when you have imported mass spectrometry data in .raw, .d, or mzXML format and need to generate a TIC plot to visualize overall sample ionization intensity as a function of retention time.
- ▌ Mass Spectrometry Adduct Annotation 3 · holobiomicslabUse when you have tabulated pairwise mass differences from a MALDI-MS imaging dataset (via massdiff()) and need to identify which observed mass differences correspond to known chemical adducts (e.g., [M+H]+, [M+Na]+, [M-H2O]+).
- ▌ Chemical Graph Connectivity Validation 2 · holobiomicslabUse when after a machine learning model has generated predicted molecular structures (connectivity graphs and molecular formulas) from 1D NMR spectra. Use it to quantify accuracy on a held-out test set, measure degradation when applying the model beyond its training scope (e.
- ▌ Dataframe And Numericlist Manipulation 2 · holobiomicslabUse when you are implementing a new MsBackend subclass and need to store spectra metadata (sample names, retention times, precursor m/z, etc.) separately from peak data (m/z and intensity pairs) while maintaining row-wise alignment.
- ▌ Feature Group Refinement Multicriteria 3 · holobiomicslabUse when after initial retention-time-based feature grouping (e.g., ±20 s window) when you need to separate co-eluting features that are chemically distinct. Triggers include: (1) large feature groups (>2–3 members) suspected to contain multiple compounds;
- ▌ Retention Time Alignment Index Mapping 3 · holobiomicslabUse when when processing multiple LC-MS samples with varying scan numbers or retention-time drift, before constructing composite mass tracks for peak detection.
- ▌ Spectral Features Module Integration 2 · holobiomicslabUse when when you have a trained or untrained chemprop base model (graph convolution + readout layers) and need to extend it to predict infrared spectral properties rather than scalar molecular properties.
- ▌ Spectral Library Matching Evaluation 2 · holobiomicslabUse when you have a trained spectral embedding model (e.g., MSBERT, Spec2Vec) and need to benchmark its library matching accuracy against reference spectra on a test dataset.
- ▌ Spectral Similarity Network Building 3 · holobiomicslabUse when when you have detected LC-MS/MS features (MS1 peaks with MS2 fragmentation spectra) from untargeted metabolomics experiments and seek to organize them into a chemical hierarchy for comparative metabolomic analysis.
- ▌ Spectrum Filtering And Normalization 3 · holobiomicslabUse when you have raw or minimally processed tandem MS spectra (in mzML, mgf, or other standard formats) and need to prepare them for spectral matching, library searching, or quantitative analysis.
- ▌ Chemical Class Novelty Detection 2 · holobiomicslabUse when when you have CANOPUS chemical class predictions for your samples and need to identify which extracts contain chemical classes absent from the literature for their species or genus.
- ▌ Abstract Base Class Implementation 2 · holobiomicslabUse when when building a visualization library that must support multiple plotting backends (e.g., matplotlib, bokeh, plotly) and multiple data types (e.g., chromatograms, spectra, peak maps) without duplicating core logic or configuration handling across backend–plot-type combinations.
- ▌ Adduct Mass Adjustment Calculation 2 · holobiomicslabUse when you have a set of in silico-predicted compounds (with SMILES structures) and an experimental metabolomics peak list (m/z values), and you need to filter predictions to only those that could plausibly be detected.
- ▌ CSV File Parsing And Peak Indexing 2 · holobiomicslabUse when you have a metabolomics dataset (CSV format) containing detected peaks with m/z values and optionally retention time windows, and you need to filter a Pickaxe-generated compound expansion to keep only compounds whose masses match these observed peaks within a specified mass tolerance.
- ▌ Datatype Validation Helper Methods 2 · holobiomicslabUse when when implementing a custom MsBackend subclass and need to verify that spectra variables (e.g., precursor m/z, retention time, MS level) conform to expected data types before exposing them to Spectra objects.
- ▌ Ft Icr Ms Analysis Tool Evaluation 3 · holobiomicslabUse when you are evaluating or selecting FT-ICR MS software for a specific metabolomics workflow and need to assess which tools support your required analytical dimensions (e.g., Van Krevelen diagrams, PERMANOVA, thermodynamic indices, chemodiversity metrics, transformation networks).
- ▌ Graph Clustering Community Detection 3 · holobiomicslabUse when after constructing a spectral similarity network from pairwise cosine similarity scores between deconvolved GC-MS spectra.
- ▌ Hydrogen Rearrangement Rules Scoring 2 · holobiomicslabUse when after MS-CleanR has filtered and clustered LC-MS features and formatted them for MS-FINDER input (m/z, retention time, MS/MS spectra).
- ▌ Interactive Visualization Inspection 2 · holobiomicslabUse when after msFeaST pipeline execution has produced a dashboard_data.json file containing quantification, metadata, and spectral matrices, or when you need to validate that preprocessing steps correctly loaded and rendered ms/ms feature data before downstream statistical or network analysis.
- ▌ Internal Standard Feature Extraction 2 · holobiomicslabUse when you have processed LC-MS run data (feature table or peak detection output) containing internal standard identifications and need to monitor internal standard retention time, m/z, and intensity variation across samples as part of automated or user-defined QC checks during instrument runs.
- ▌ Ion Mobility Arrival Time Conversion 2 · holobiomicslabUse when you have a feature table containing raw ion mobility arrival time measurements paired with experimentally assigned biomolecular class labels (e.g., lipid, protein, carbohydrate), and you need to compute CCS values for downstream structural or comparative analysis.
- ▌ Isotopologue Mass Offset Calculation 2 · holobiomicslabUse when you have a peak-picked feature table (HDF5 format with m/z, drift_time, retention_time, intensity columns) and need to identify and label isotopic signatures within singly charged species.
- ▌ Jupyter Notebook Workflow Automation 3 · holobiomicslabUse when when you have raw LC-MS/MS spectral data in .
- ▌ Lc Hrms Metabolomics Data Processing 3 · holobiomicslabUse when you have LC-HRMS raw data files (.mzML or .abf format) from metabolomics experiments and need to extract, align, and annotate features in a reproducible manner across multiple computational environments.
- ▌ Lc Ms Scan Acquisition Orchestration 3 · holobiomicslabUse when when you have a curated list of chemical compounds (real or virtual), a defined fragmentation strategy (e.g., Top-N, exclusion lists), and need to simulate how that strategy will acquire MS1 and MS2 scans over a defined retention-time window.
- ▌ Mass Spectral Fingerprint Generation 3 · holobiomicslabUse when you have unaligned MS2 spectra from one or more samples (in formats like .mgf, .mzML, or .mzXML) and need to compare them in a retention-time-agnostic manner.
- ▌ Mass Spectral Metadata Harmonization 3 · holobiomicslabUse when you have multiple mass spectral libraries in different formats (NIST MSP + MOL folder, MoNA MSP, RIKEN MSP, SWGDRUG MSP) and need to merge them into a single, MS-DIAL-compatible MSP file with consistent SMILES assignments, Kovats retention indices (RI), and polarity annotations across all.
- ▌ Mass Spectrometry Benchmark Analysis 3 · holobiomicslabUse when you have implemented or modified a tandem mass spectrometry formula inference model and need to measure whether a specific architectural change (e.
- ▌ Mass Spectrometry Data Visualization 3 · holobiomicslabUse when after applying retention time, abundance correlation, or EIC similarity-based feature grouping (e.g., via SimilarRtimeParam, AbundanceSimilarityParam, or EicSimilarityParam). Use when you need to visually confirm that grouped features belong to the same compound—i.
- ▌ Mass Spectrometry Metric Engineering 3 · holobiomicslabUse when you have raw DIA mass spectrometry files (.raw, .d, .wiff formats) from timsTOF, TripleTOF, or Orbitrap instruments and need to quantify file quality for automated quality control, longitudinal instrument monitoring, or training a quality prediction classifier.
- ▌ Metabolite Identification Validation 2 · holobiomicslabUse when you have extended a metabolite identification tool (such as Met-ID) to support a new derivatizing matrix beyond the default (e.
- ▌ Metabolomic Feature Table Imputation 3 · holobiomicslabUse when after feature detection and peak alignment have produced a feature table with zero or missing values across samples.
- ▌ Spectrum Preprocessing Precursor Masking 2 · holobiomicslabUse when when training a formula-prediction model with a frozen pretrained TCN spectrum encoder and unfrozen FormulaEncoder and RescoreHead components, or when you suspect the model may use precursor intensity as a spurious feature rather than fragment-pattern information for molecular formula.
- ▌ Tandem Mass Spectra Embedding Generation 2 · holobiomicslabUse when you have tandem mass spectra (in .msp or compatible format) from instruments like Orbitrap, and you need to compute library matching scores, cluster spectra by chemical similarity, or embed spectra into a learned vector space for downstream similarity or clustering tasks.
- ▌ Graph Neural Network Model Inference 3 · holobiomicslabUse when you have a trained GNN model (stored as .h5 weights) and molecular graph representations (SMILES strings and/or 3D coordinates), and you need to compute predicted CCS values or perform feature importance analysis via ablation or gradient-based saliency mapping.
- ▌ Batch Effect Correction And Adjustment 2 · holobiomicslabUse when your m/z peak data spans multiple batches (recorded in metadata as a batch ID column) or samples have varying concentrations that are documented in metadata.
- ▌ Chemical Structure Similarity Matching 3 · holobiomicslabUse when you have a set of query chemical compounds (as SMILES, names, or ChemMine objects) and a reference library organized into type groups (e.g., Type A–E chemical sets), and you need to assign each query compound to its -matching type based on structural similarity.
- ▌ Quality Control Threshold Optimization 2 · holobiomicslabUse when when you have extracted a peak feature table (CSV or tabular format) with mass-to-charge ratios, retention times, and intensity values across multiple samples, and you need to distinguish genuine differential metabolic signals from instrumental noise or low-abundance background before.
- ▌ Spectra Data Extraction And Subsetting 3 · holobiomicslabUse when when you need to extract m/z and intensity peak values from a Spectra object backed by MsBackendMzR or similar on-disk backends; when analyzing subsets of spectra without loading all peaks into memory;
- ▌ Spectrum Record Consistency Validation 3 · holobiomicslabUse 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 to verify that all implementations produce identical spectrum metadata, data types, row counts, and numerical values.
- ▌ Hierarchical Spectrum Object Construction 2 · holobiomicslabUse when immediately after parsing and validating raw LC-MS/MS data files (mzML, mzXML, or vendor formats) when you need to prepare spectral data for fragmentation tree computation, isotope pattern analysis, or molecular formula ranking within the SIRIUS framework.
- ▌ Mass Spectrometry Metadata Interpretation 2 · holobiomicslabUse when when integrating LC-MS/MS data from diverse sources (e.g., public repositories like MSV000080102, instrument outputs, or precomputed workflows) into NPDtools pipelines.
- ▌ Signal Trend Assessment Across Injections 2 · holobiomicslabUse when you have QCpool (pooled quality control) samples measured at regular intervals across one or more LC-MS/MS sequences and need to detect whether instrument performance degrades, drifts, or destabilizes during the analytical run.
- ▌ Top N Accuracy And Auc Metric Calculation 2 · holobiomicslabUse when you have a ranked candidate list (e.g., BGCs sorted by IOKR or strain-correlation score) for each test spectrum, a known ground-truth BGC for each spectrum, and you want to measure retrieval performance across multiple recall depths (top-1 through top-200) and overall discrimination.
- ▌ Bgc Spectrum Ranking By Kernel Similarity 3 · holobiomicslabUse when you have: (1) a trained IOKR model mapping from spectrum kernels to molecular fingerprints, (2) MS2 spectra from your sample, (3) a set of candidate BGCs with known or predicted structures (e.
- ▌ Chemical Structure Fingerprint Comparison 4 · holobiomicslabUse when when you have MS/MS spectra with known chemical structures (InChIKeys or SMILES) and want to validate whether a novel or existing spectral similarity scoring method actually reflects true chemical structural similarity.
- ▌ Chemo Informatics Workflow Reconstruction 2 · holobiomicslabUse when when you have access to the source code of a chemo-informatics tool (e.
- ▌ Comparative Machine Learning Benchmarking 3 · holobiomicslabUse when you have developed a new machine learning model for predicting metabolomic profiles from microbiome data and need to quantify its performance improvement over existing methods.
- ▌ Precursor Ion Chromatogram Extraction 3 · holobiomicslabUse when you have raw DIA mass spectrometry data files (.raw, .d, or .wiff formats) from timsTOF, TripleTOF, or Orbitrap instruments and need to extract precursor ion chromatograms for quality assessment or downstream analysis.
- ▌ Precursor Peak Removal Mass Tolerance 3 · holobiomicslabUse when after loading an MsmsSpectrum object but before intensity filtering or spectral annotation.
- ▌ Reaction Propensity Score Computation 3 · holobiomicslabUse when you have measured intracellular metabolite abundances (LC-MS or similar) across multiple cell lines or conditions and a stoichiometric metabolic model (with reaction-metabolite associations) to estimate how differences in substrate availability—independent of gene expression—translate into.
- ▌ Retention Time And Mz Based Alignment 3 · holobiomicslabUse when after peak detection has been completed on individual LC-MS samples and you have a collection of detected peaks with m/z, retention time, and intensity values from each sample.
- ▌ Routing Module Testing And Validation 3 · holobiomicslabUse when when you have implemented conditional routing logic in the GNPS_MASST codebase and need to verify that spectrum submissions with explicit domain-context selections (e.
- ▌ Sparse Distance Matrix Interpretation 2 · holobiomicslabUse when you have computed a sparse pairwise distance matrix from nearest neighbor indexes (containing only cosine distances between neighboring spectra, not exhaustive pairwise comparisons) and need to partition spectra into groups of similar ions or peptides.
- ▌ Spectral Peak Intensity Normalization 2 · holobiomicslabUse when after loading raw m/z peak data (in MetaboAnalyst, MetaboShiny native, or Metabolights format) and merging it with sample metadata (batch IDs, concentration values, experimental group labels).
- ▌ Spectral Peak Matching With Tolerance 2 · holobiomicslabUse when when comparing a query MS/MS spectrum (e.g., from an unknown metabolite) against a library spectrum to establish correspondence between peaks. Use this skill before calculating similarity scores (cosine, entropy, Bhattacharyya) or when applying penalty factors to unmatched peaks.
- ▌ Spectral Similarity Scoring Ei Simple 2 · holobiomicslabUse when you have a query electron ionization (EI) mass spectrum and need to search it against a library of known EI mass spectra to identify unknown compounds. Use it when exact identity matching (e.
- ▌ Subformula Assignment Neural Networks 3 · holobiomicslabUse when when you have MS/MS spectra with assigned precursor formulas and need to annotate fragment peaks with their chemical subformulas, but want to avoid the computational overhead of generating full SIRIUS fragmentation trees or do not have access to spectrum databases.
- ▌ Substrate Concentration Normalization 2 · holobiomicslabUse when you have LC-MS normalized intracellular metabolite abundance data from multiple cell lines (or samples) and need to compute reaction-level propensity scores that account for substrate availability as a predictor of metabolic flux.
- ▌ Tanimoto Score Threshold Optimization 3 · holobiomicslabUse when when you have a set of MS/MS spectra with ground-truth structural similarity labels (Tanimoto scores computed from molecular fingerprints) and need to choose a decision threshold for classifying spectrum pairs as 'chemically related' or 'unrelated'.
- ▌ Temporal Profile Correlation Analysis 3 · holobiomicslabUse when you have time-resolved direct injection mass spectrometry data (e.
- ▌ Transformer Encoder Decoder Inference 2 · holobiomicslabUse when when you have preprocessed MS/MS spectra (normalized intensities, filtered for quality, with top peaks retained) that have been encoded using a spectral representation method (e.
- ▌ Atom Feature Extraction Chemistry 3 · holobiomicslabUse when you have canonicalized SMILES strings from a chemical database (e.
- ▌ Metabolomics Feature Table Filtering 3 · holobiomicslabUse when when you have a raw LC-MS peak table imported from vendor software (e.
- ▌ Molecular Formula Quality Assessment 2 · holobiomicslabUse when immediately after formula assignment from raw FT-ICR MS peak detection, when you have a peak intensity matrix with assigned molecular formulas and need to remove spurious or low-confidence assignments before calculating thermodynamic indices, determining compound classes, or performing.
- ▌ Molecular Network Graph Manipulation 3 · holobiomicslabUse when you have a GNPS-generated classical or feature-based molecular network (in graphml or JSON format) and corresponding MS2LDA or chemical class assignment data, and you need to embed substructural motif identifiers, confidence scores, or chemical class labels as node/edge attributes for.
- ▌ Msconvert Integration And Invocation 2 · holobiomicslabUse when when you have vendor-format LC-MS acquisition files (Thermo .raw, Bruker .d, Sciex .ms, Agilent, Waters formats) that need to be ingested into a quality control or data processing pipeline that requires open, standardized spectral formats.
- ▌ Multi Dataset Integration Mzrt Space 2 · holobiomicslabUse when you have multiple CSV feature tables from independent metabolomic experiments, each with RT and m/z annotations, and you need to produce a single consolidated feature matrix for comparative analysis across all samples.
- ▌ Multi Task Loss Function Formulation 2 · holobiomicslabUse when when training an object detection network that must predict both discrete labels (e.g., true peak vs. false peak) and continuous coordinates (e.
- ▌ Neural Network Architecture Training 2 · holobiomicslabUse when you have a pretrained TCN spectrum encoder from formula prediction and need to train a rescoring model that ranks formula candidates by confidence. The input is a set of spectra with ground-truth formula labels and multiple candidate formulas per spectrum.
- ▌ Prm Acquisition Event Identification 4 · holobiomicslabUse when you have a Thermo Fisher Scientific .raw file containing PRM data and need to verify that acquisition of a specific precursor ion (e.g., LGGNEQVTR++ at m/z 487.2567) is happening at regular intervals consistent with your instrument method design.
- ▌ Qc Reference Chromatogram Extraction 2 · holobiomicslabUse when when processing a batch of LC-MS samples in mzML or mzXML format where at least one file has been designated as a quality control (QC) file, extract its TIC or BPC before performing retention time correction.
- ▌ Retention Time Prediction Validation 2 · holobiomicslabUse 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.
- ▌ Sample Centric Metabolite Annotation 3 · holobiomicslabUse when after MZmine feature detection and molecular networking on a single LC-MS/MS DDA sample, when you have a feature table (with retention time, m/z, fragmentation spectra) and sample-level taxonomical metadata, and you want to assign both spectral identity and predicted chemical structure to.
- ▌ Sampledata Annotation And Assignment 2 · holobiomicslabUse when after loading multiple LC-MS .mzML files into an MsExperiment object using MsBackendMzR backend, when you have a documented injection sequence (e.
- ▌ Search Results Filtering And Parsing 2 · holobiomicslabUse when you have loaded DIA mass spectrometry search results containing feature identification data with associated Q-value scores, and you need to restrict the analytes available in selection drop-downs to those meeting a quality cutoff (typically 1% FDR equivalent) before visualization or manual.
- ▌ Simulation Control Loop Architecture 4 · holobiomicslabUse 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 window selection) would perform without access to real instrument time.