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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Noise Suppression Spectral Imaging · holobiomicslab

   Use when your input is a raw two-dimensional MS map (m/z vs retention time) derived from chromatography–mass spectrometry data with poor signal-to-noise characteristics, and you need to discriminate individual analytes and identify marker features reliably.
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2. ▌
   Pure Component Spectrum Extraction · holobiomicslab

   Use when analyzing GC-MS data containing overlapped peaks where two or more components co-elute within the same retention time window, making direct spectral assignment impossible.
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3. ▌
   Quality Control Sample Aggregation · holobiomicslab

   Use when you have a feature intensity matrix (peak vector) and a corresponding set of QC sample indices from a multi-batch LC/GC-MS experiment, and you need to establish batch-invariant reference statistics before applying QC-based batch correction methods such as bcpareto(), bccenter(), or.
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4. ▌
   R Object Inspection And Validation · holobiomicslab

   Use when after performing assignment operations (assign_ri, assign_smiles) or combining multiple library objects (e.
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5. ▌
   Sample Capacity Constraint Setting · holobiomicslab

   Use when when designing injection sequences for LC/GC-MS multi-omics experiments where you need to distribute samples across multiple plates and must account for mandatory QC sample positions (Blank QC, Solvent QC, Pooled QC, Long-Term Reference QC, and custom QC).
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6. ▌
   Spectral Adduct Ionmode Validation · holobiomicslab

   Use when when processing raw or aggregated mass spectra datasets (from .mgf, .msp, .json, or .
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7. ▌
   Adduct Based Feature Consolidation · holobiomicslab

   Use when after accurate mass searching has assigned multiple detected m/z features to the same metabolite via positive and negative adduct libraries, and before sample-level feature merging.
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8. ▌
   Adduct Fragment Table Construction · holobiomicslab

   Use when when initializing an mWISE annotation pipeline with a new or custom KEGG database, or when you need to reconstruct the Cpd.Add matching table with modified adduct/fragment specifications (e.g., subset to instrument-specific adducts or adjust frequency thresholds).
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9. ▌
   Algorithm Performance Benchmarking · holobiomicslab

   Use when you have refactored or reimplemented a core computational method (e.g., entropy similarity calculation) and need to verify that the new implementation produces mathematically equivalent results to the original before deploying it to production.
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10. ▌
    Aligned Feature Table Manipulation · holobiomicslab

    Use when after multi-sample alignment has been completed in JPA (Part 5), when you have an aligned feature table containing consolidated features across samples and need to extract ion chromatograms, perform CAMERA annotation, or validate feature assignments prior to MS2 annotation.
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11. ▌
    Attention Mechanism Implementation · holobiomicslab

    Use when you have imaging mass spectrometry (IMS) datasets with peak intensity features organized as spatial graphs (nodes = pixels/voxels, edges = spatial adjacency), and you need to discover latent peak patterns for automatic peak picking or marker ion identification without manual feature.
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12. ▌
    Background Ion Contaminant Removal · holobiomicslab

    Use when you have a feature table from LC-MS data alongside blank (solvent-only) sample runs, and you want to remove features whose intensity in study samples is not substantially higher than their intensity in blanks.
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13. ▌
    Batch Normalization Implementation · holobiomicslab

    Use when apply batch normalization after dense hidden layers (but not the final embedding layer) in a deep neural network trained on MS/MS spectral data, particularly when the network processes high-dimensional binned spectra (9948-dimensional vectors) and you need to stabilize gradient flow across.
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14. ▌
    Categorical Ion Status Aggregation · holobiomicslab

    Use when after running qc_summary() on a filtered mpactr object when you need to understand the distribution of ions across filter status categories (passed vs. failed filters) and want to visualize or report the count and percentage composition of each status group.
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15. ▌
    Ccs Calibration Polynomial Fitting · holobiomicslab

    Use when you have acquired tunemix or reference standard data in ion mobility spectrometry with known m/z, drift time, and CCS values, and you need to establish a drift-time-to-CCS mapping for a specific instrument, ionization mode (positive or negative), and buffer gas.
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16. ▌
    Chromatographic Data Visualization · holobiomicslab

    Use when after peak detection has been completed and a feature table has been generated in MetCohort.
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17. ▌
    Chromatographic Feature Extraction · holobiomicslab

    Use when you have centroided mzML files from LC- or GC-HRMS instruments (acquired in data-dependent mode with ddMS2) and need to systematically identify chromatographic peaks, measure their mass and retention time coordinates, and quantify their intensities before applying PFAS-specific.
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18. ▌
    Chromatographic Feature Refinement · holobiomicslab

    Use when after performing retention-time-based grouping on LC-MS data (e.g., with a 10–20 second window) and observing that many feature groups contain features with similar retention times but dissimilar abundance patterns across samples or different extracted ion chromatogram peak shapes.
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19. ▌
    Cnn Inference On Metabolomics Data · holobiomicslab

    Use when you have LC-MS feature tables (with m/z and retention time columns) paired with raw .mzXML or .mzML files, and you need to automatically validate which detected features correspond to genuine chromatographic peaks versus false positives or noise.
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20. ▌
    Compound Identification From Ms Ms · holobiomicslab

    Use when you have LC-MS/MS data in mgf format and a custom spectral database prepared with CFM-id (or an in-built database), and you need to identify unknown compounds by comparing their experimental fragmentation patterns against predicted or reference spectra with quantified match scores.
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21. ▌
    Compound Identification Validation · holobiomicslab

    Use when when you have an unknown MS/MS spectrum (in .
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22. ▌
    Conditional Dispatch Routing Logic · holobiomicslab

    Use when a mass spectrometry analysis pipeline must accept data from multiple sources with different identifier schemes (GNPS Task ID, Universal Spectrum Identifiers, or Feature-Based Molecular Networking task IDs), and you need to transparently route each to the correct loader without requiring.
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23. ▌
    Controlled Vocabulary Term Mapping · holobiomicslab

    Use when you have collected or inherited sample-information metadata from multiple sources (e.
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24. ▌
    Corpus Bag Of Words Representation · holobiomicslab

    Use when when you have raw LC-MS/MS data in MGF format and need to prepare it for unsupervised topic modeling of metabolomics fragmentation patterns.
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25. ▌
    Data Interchange Format Conversion · holobiomicslab

    Use when you have deconvoluted or processed MS/MS spectra from SWATH-MS data that need to be (1) ingested into tools requiring open formats (e.g., spectral library matching, metabolite identification pipelines), (2) archived in public repositories, or (3) shared across different analysis platforms.
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26. ▌
    Dataset Size Threshold Enforcement · holobiomicslab

    Use when when you have partitioned public MS/MS files from MassIVE using the ReDU File Selector into one or more filtered groups (G1–G6) and need to verify that each group's file count complies with computational constraints before submitting to GNPS molecular networking (3000 file limit) or.
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27. ▌
    Deep Learning Model Initialization · holobiomicslab

    Use when you have downloaded the LC-MS spectral peak dataset (DOI 10.25345/C5FD2F) and need to train a DNN model from scratch rather than using a pre-trained checkpoint.
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28. ▌
    Difference Count Table Integration · holobiomicslab

    Use when when analyzing tandem MS/MS spectra with SIMILE V2 and you want to leverage both fragment ion mass differences and neutral loss patterns to improve spectral similarity scoring.
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29. ▌
    Dropout Regularization Application · holobiomicslab

    Use when when training a deep neural network on mass spectrometry spectral data where overfitting is a risk (especially with data augmentation applied), and when you need both regularization during training AND uncertainty quantification at inference time via multiple forward passes with dropout.
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30. ▌
    Feature Abundance Pattern Matching · holobiomicslab

    Use when after initial retention-time-based feature grouping when you have groups of multiple features at similar m/z and retention time but need to determine which features actually arise from the same compound.
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31. ▌
    Feature Clustering Intensity Based · holobiomicslab

    Use when after matching mass-to-charge ratios to a KEGG database and obtaining multiple candidate metabolites per feature, but before filtering quasi-molecular adducts.
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32. ▌
    Feature Pairing Confidence Scoring · holobiomicslab

    Use when you have two LC-MS feature tables (each with m/z, retention time, and intensity columns) and need to establish reliable correspondence between features across datasets.
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33. ▌
    Feature Quality Assessment Metrics · holobiomicslab

    Use when after nontargeted peak detection and segmentation has generated a feature table from raw LC-MS data (mzML or vendor format), apply quality assessment when you need to rank or filter features by confidence before annotation, adduct grouping, or MS/MS matching.
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34. ▌
    Feature Table Row Count Validation · holobiomicslab

    Use when after peak quality filtering has been applied to a composite map peak detection output using SNR (>2), goodness-of-fit (peakshape > 0.5), minimum peak height (default 1e5), and prominence (≥20% of peak_height) thresholds.
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35. ▌
    File Format Parsing And Validation · holobiomicslab

    Use when you have peak/feature tables from one or more of MZmine, XCMS, MS-DIAL, or Compound Discoverer and need to ingest them into LipidMatch for lipid identification. The input files are in tabular format (CSV, TSV, or Excel) and their upstream tool origin may be unknown or mixed.
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36. ▌
    File Grouping By Sample Attributes · holobiomicslab

    Use when you have a validated ReDU sample-information metadata table (gnps_metadata.tsv) loaded from a MassIVE accession, and you need to partition public MS/MS files into multiple analysis cohorts by one or more sample attributes.
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37. ▌
    Formula Accuracy Metric Evaluation · holobiomicslab

    Use when when training or validating a deep learning model for molecular formula prediction from tandem MS/MS spectra, use this metric to track whether the model's predicted formula (including hydrogen atoms) exactly matches the annotated ground-truth formula.
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38. ▌
    Formula Based Network Construction · holobiomicslab

    Use when you have a formula-assigned dataset from FT-ICR MS (or other compound-annotated mass spectrometry) and you want to characterize molecular transformations and their co-occurrence patterns—particularly in studies of DOM reactivity, fermentation, or oxidative treatment of organic mixtures.
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39. ▌
    Formula Network Extraction From Mz · holobiomicslab

    Use when you have an observed m/z value from spatially-resolved mass spectrometry imaging and need to assign one or more plausible molecular formulae with confidence metrics.
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40. ▌
    Fragment Level Spectrum Prediction · holobiomicslab

    Use when when you have a molecular structure (SMILES, InChI, or chemical formula) and need to predict its tandem mass spectrum for structural elucidation or mass spectrometry validation.
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41. ▌
    Fragmentation Spectrum Ion Pairing · holobiomicslab

    Use when you have two MS/MS spectra (precursor m/z and fragment ion lists) and need to identify the non-overlapping set of fragment ion alignments. Use this skill when: (1) you want to move beyond monotonic alignment to capture complex ion relationships;
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42. ▌
    Generalized Additive Model Fitting · holobiomicslab

    Use when when a feature table from LC-MS metabolomic profiling contains QC (quality control) sample annotations and exhibits systematic signal drift correlated with run order or batch number.
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43. ▌
    Genome Identifier Organism Mapping · holobiomicslab

    Use when a paired omics project record contains a genome identifier field (e.g., from GenBank) but lacks the corresponding organism name, or when you need to validate that genome identifiers in bulk project records can be resolved to authoritative taxonomy.
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44. ▌
    Gnps Molecular Network Integration · holobiomicslab

    Use when you have computed frequent fragmentation patterns from a collection of MS/MS spectra using mineMS2, and you want to focus pattern interpretation on subsets of spectra that form meaningful network components (connected groups, cliques, or high-similarity pairs) in a GNPS molecular network.
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45. ▌
    Gnps Workflow Identifier Retrieval · holobiomicslab

    Use when when you have a GNPS molecular networking task ID and need to fetch the job archive, decompose it into standard metabolomics file formats (spectra.mgf, molecular_families.tsv, annotations.tsv, file_mappings), and prepare them for integration with genomics data.
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46. ▌
    Gradient Space Optimization Search · holobiomicslab

    Use when after fitting a Gaussian Process regression model to prior LC-MS gradient runs (retention times, separation efficiency scores, or compound identification counts).
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47. ▌
    Hyperparameter Sweep Configuration · holobiomicslab

    Use when when implementing multiple competing model architectures (e.
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48. ▌
    Instrument Metadata Classification · holobiomicslab

    Use when when preprocessing a heterogeneous spectral library (e.g., GNPS public library) that contains spectra from multiple instrument types, and you need to partition data by a single instrument class to train or evaluate a formula-prediction model.
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49. ▌
    Ion Mobility Heatmap Visualization · holobiomicslab

    Use when you have raw LC-IMS-MS data (Agilent, Thermo, Bruker, or mzML format) and need to visualize and export the spatial distribution of a specific ion species (or ion family) across both ion mobility and retention time dimensions.
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50. ▌
    Isf Relationship Tree Construction · holobiomicslab

    Use when after completing ISFrag Part 4 (Identification of ISF Features) when you have a validated feature table with identified ISF features and need to visualize or export the hierarchical fragmentation structure linking parent ions to their in-source fragments.
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51. ▌
    Isotopic Enrichment Quantification · holobiomicslab

    Use when you have MS2 spectra from peptides with known stable isotope enrichment (e.g., 52% ¹³C incorporation), a target peptide sequence, and you need to determine which B and Y ion fragments carry how many isotope labels at each position.
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52. ▌
    JSON Serialization Deserialization · holobiomicslab

    Use when when you have completed a computational step (e.g., corpus feature extraction or gensim LDA inference) and need to persist the result for later retrieval, pass it to a separate process (e.g., Celery task), or load it into a database.
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53. ▌
    Kegg Candidate Network Integration · holobiomicslab

    Use when after cluster-based filtering has produced a set of candidate KEGG compounds for each feature cluster in untargeted LC-MS data, and you need to rank these candidates by their metabolic plausibility using network context rather than mass accuracy alone.
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54. ▌
    Knowledge Graph Integration Design · holobiomicslab

    Use when designing a metabolite annotation workflow that must simultaneously leverage established biochemical knowledge (pathway databases, reaction networks) and experimental evidence (mass spectrometry feature similarity, co-occurrence patterns).
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55. ▌
    Lc Hrms Data Processing Evaluation · holobiomicslab

    Use when you have processed the same set of untargeted LC/HRMS files (mzXML, mzML, or netCDF format) with two or more peak-picking tools and need to validate which tool produces higher-quality peaklists for organic small molecules.
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56. ▌
    Lcms Peak Alignment And Annotation · holobiomicslab

    Use when you have an XCMS-processed feature set (XCMSet object) from replicate LC/MS runs comparing labeled (e.g., 13C-glucose) and unlabeled (e.g., 12C-glucose) conditions, and need to identify which features show isotope incorporation (fold-change ≥1.5, p-value <0.
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57. ▌
    Lipid Library Format Specification · holobiomicslab

    Use when when you have curated or synthesized a set of custom lipid species (e.g., rare or organism-specific lipids, modified lipids, or synthetic standards) and need to integrate them into LipidMatch for candidate matching against your experimental MS/MS datasets.
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58. ▌
    Mass Grid Construction And Mapping · holobiomicslab

    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. Specifically: when study size is ≤10 samples, use pairwise anchor-prioritized alignment;
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59. ▌
    Mass Spectrometry Library Curation · holobiomicslab

    Use when when preprocessing a public MS/MS spectral library (e.g., GNPS) for machine learning and you discover discrepancies between expected and observed compound counts after filtering by instrument type, or when a known instrument metadata issue (e.
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60. ▌
    Mass Spectrometry Library Indexing · holobiomicslab

    Use when you have a large MS/MS experiment (mzML format) requiring lipid annotation and need to match experimental spectra against >10 million theoretical lipid fragments.
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61. ▌
    Mass Spectrometry Metadata Caching · holobiomicslab

    Use when you plan to perform repeated queries or filtering on MS metadata attributes (e.g., extract all MS2 spectra with collision energy > 30 eV, or collect all scans in a retention time window) across a large MZA HDF5 file.
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62. ▌
    Mass Spectrum Embedding Generation · holobiomicslab

    Use when you have cleaned MS/MS spectra (in formats like .mgf, .msp, .
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63. ▌
    Matrix Structure Validation And Qc · holobiomicslab

    Use when after executing memo_from_unaligned or memo_from_aligned functions to generate a MemoMatrix object from MS2 spectra or aligned feature tables.
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64. ▌
    Metabolite Feature Extraction Xcms · holobiomicslab

    Use when you have one or multiple raw mzXML/mzML files from DDA, DIA, or full-scan LCMS analyses and need to detect, align, and quantify metabolite features across samples to create a unified feature matrix before MS2 annotation or in-source fragment analysis.
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65. ▌
    Metabolite Library Curation Ms1 Rt · holobiomicslab

    Use when when you have processed authentic standards with LC-MS in positive and negative ESI modes, converted results to .mzML format, and need to build a validated in-house reference library with MS1 m/z and RT measurements for use in untargeted metabolomics compound identification workflows.
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66. ▌
    Metabolite Mass Lookup Preparation · holobiomicslab

    Use when when beginning an untargeted LC-MS annotation workflow, before attempting to match experimental m/z peaks to metabolite identities.
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67. ▌
    Metabolite Set Decomposition Plage · holobiomicslab

    Use when you have peak intensity data from metabolomics experiments with annotated metabolites assigned to known groupings (KEGG pathways, Reactome, GNPS Molecular Families, or MS2LDA Mass2Motifs) and need to identify which metabolite sets change significantly across experimental comparisons while.
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68. ▌
    Metabolomic Feature Table Assembly · holobiomicslab

    Use when when you have LC-MS data (mzML or netCDF format) and a pre-defined list of target metabolites (m/z, retention time, and identifiers) that you wish to extract and quantify across multiple samples, rather than performing untargeted feature discovery.
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69. ▌
    Metabolomics Data Input Validation · holobiomicslab

    Use when when importing a tab-delimited or Sciex OS text export metabolomics dataset into mzQuality, before building the SummarizedExperiment object.
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70. ▌
    Metabolomics Feature Preprocessing · holobiomicslab

    Use when when you have raw profile LC-MS data in .mzML format and need to prepare regions of interest (ROI) as input for a CNN-Transformer peak detection network.
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71. ▌
    Metabolomics Scan Metadata Linking · holobiomicslab

    Use when after running a ViMMS Environment simulation with save_eval flag enabled, when you need to preserve the link between each simulated MS/MS scan in the output mzML file and its source chemical definition, fragmentation parameters, and evaluation metrics for later analysis, comparison, or.
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72. ▌
    Modularity Optimization Clustering · holobiomicslab

    Use when after MS-DIAL peak character estimation has grouped LC-MS features into preliminary clusters based on peak shape and chromatographic similarity, and you need to select a single representative parental feature from each cluster to reduce redundancy before MS-FINDER annotation.
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73. ▌
    Molecular Family Grouping Analysis · holobiomicslab

    Use when you have untargeted metabolomics peak intensity data and spectral groupings (Molecular Families or Mass2Motifs) but lack confident chemical annotations or want to avoid pathway database dependency.
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74. ▌
    Motifdb Reference Library Querying · holobiomicslab

    Use when after Mass2Motifs have been inferred from tandem MS/MS spectra via LDA topic modeling and you need to assign putative substructure annotations to those motifs.
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75. ▌
    Ms Ms Feature Preparation For Gnps · holobiomicslab

    Use when you have completed LC-MS/MS data processing and feature alignment in MZmine2 or Optimus, generated a feature quantification matrix and MGF file, and now need to format these outputs for submission to GNPS to compute spectral similarity networks and retrieve node/edge tables.
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76. ▌
    Ms Ms Similarity Metric Comparison · holobiomicslab

    Use when when you have MS/MS spectra from both query compounds and a reference library and need to decide which similarity metric will maximize identification accuracy (true positive rank, precision@k) or when benchmarking a new compound identification workflow against a known-good reference.
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77. ▌
    Ms Ms Spectrum Pairwise Comparison · holobiomicslab

    Use when you have millions of MS/MS spectra in mzML, mzXML, or MGF format that have been converted to low-dimensional vectors via feature hashing, and you need to identify which spectra are similar enough to cluster together.
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78. ▌
    Ms Spectral Similarity Calculation · holobiomicslab

    Use when when comparing two or more MS/MS spectra for compound identification, library matching, or spectral validation. Triggered when raw spectral data requires quantitative similarity assessment before database lookup, or when validating that two spectra originate from the same chemical compound.
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79. ▌
    Ms1 Feature Ranking And Extraction · holobiomicslab

    Use when when you have raw LC-MS data files and need to identify which compounds were actually detected at high abundance during a gradient run, prior to evaluating whether the gradient provided good separation across the chemical space.
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80. ▌
    Ms2 Fragmentation Spectrum Parsing · holobiomicslab

    Use when you have raw MS2 spectra in common formats (mzML, mzXML, msp, MGF, JSON) and need to convert them into normalized, queryable spectral objects for downstream analysis such as MS2 fingerprinting, spectral similarity scoring, or sample comparison.
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81. ▌
    Ms2 Spectral Dissimilarity Scoring · holobiomicslab

    Use when you have MS2 fragmentation spectra from multiple metabolomics samples and need to identify samples with unusual spectral profiles that may indicate novel chemistry, independent of feature abundance or annotation status.
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82. ▌
    Msexperiment Backend Configuration · holobiomicslab

    Use when you have multiple centroided .mzML LC-MS files that need to be loaded into a unified object for targeted peak integration, and you need to distinguish QC runs from sample runs to compute per-group quality metrics (e.g., average SNR, peak correlation, area under curve per QC cohort).
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83. ▌
    Multidimensional Scaling Embedding · holobiomicslab

    Use when after computing a pairwise sample distance matrix from aligned MS2 fingerprint vectors and you need to visualize sample relationships, clustering, or separation by group identity in 2D space.
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84. ▌
    Multiformat Data Export To PDF CSV · holobiomicslab

    Use when you have raw MS data in vendor formats (Agilent .d, Thermo .raw, Bruker .
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85. ▌
    Multiplexed Spectrum Decomposition · holobiomicslab

    Use when you have SWATH-MS data (mzML or vendor binary format) where precursor isolation windows intentionally capture multiple co-eluting compounds, resulting in multiplexed MS/MS spectra that contain mixed fragment ion peaks from unknown metabolites.
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86. ▌
    Mztab Format Export And Annotation · holobiomicslab

    Use when after Casanovo has generated ranked peptide sequence predictions from MS/MS spectra and you need to persist, share, or integrate the results into a proteomics data management or visualization pipeline.
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87. ▌
    Neural Network Architecture Design · holobiomicslab

    Use when you have raw mzML files and feature tables (CSV from mzMine or XCMS) for LCMS data, have generated training/validation/test batches with known class imbalance, and need to train a CNN model from scratch to achieve AUC ROC > 0.9 for distinguishing true from false positive MS1 peaks.
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88. ▌
    Neural Network Inference Execution · holobiomicslab

    Use when you have (1) a molecular structure input in SMILES, InChI, or chemical formula format, (2) a pretrained ICEBERG model checkpoint with fragment generation and intensity prediction weights, and (3) a goal to predict fragmentation patterns and m/z intensities for unknown compound.
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89. ▌
    Numerical Equivalence Verification · holobiomicslab

    Use when when you have reimplemented an algorithm in a new package or optimized an existing algorithm and need to verify that the new version produces the same numerical results as the original or reference implementation.
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90. ▌
    Peak Height Threshold Optimization · holobiomicslab

    Use when you have raw metabolomic LC-MS data processed through XCMS CentWave feature extraction and want to improve true positive feature recovery while controlling false positive rate and crash likelihood.
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91. ▌
    Peak Property Preparation From CSV · holobiomicslab

    Use when you have a CSV file containing nucleoside or peptide molecular data (formulas, identifiers, retention times, intensities) that you want to simulate as LC-MS/MS runs. Use this skill as the mandatory first step before selecting a fragmentation model and noise injector in SMITER.
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92. ▌
    Peak Selectivity Metric Evaluation · holobiomicslab

    Use when when identifying landmark peaks for retention time alignment in multi-sample LC-MS metabolomics workflows.
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93. ▌
    Peak To Formula Assignment Mapping · holobiomicslab

    Use when when you have a fragment peak list (m/z values and intensities) from MS/MS data and need to assign candidate chemical subformulae to each peak as part of a de novo chemical formula inference pipeline.
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94. ▌
    Precursor Fragment Pairing For Mrm · holobiomicslab

    Use when when designing a targeted lipidomics experiment and you have lipid species definitions (including chain composition and adducts) but need to configure precursor–fragment transitions for MRM or PRM acquisition on a Thermo QExactive HF, Agilent QTOF, or compatible high-resolution or.
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95. ▌
    Precursor Mass Tolerance Filtering · holobiomicslab

    Use when after cosine similarity or dot-product scoring of experimental MS/MS spectra against a reference library, when you need to eliminate matches whose precursor m/z values deviate too far from the experimental precursor m/z, thereby improving specificity of library matching before final.
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96. ▌
    Proprietary Data Structure Mapping · holobiomicslab

    Use when you have received raw mass spectrometry data in one of four proprietary vendor formats (Agilent '.d', Bruker ion mobility 'd', Thermo '.raw', or mzML) and need to convert it to a cross-platform, cross-language accessible format.
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97. ▌
    Q Value Based Confidence Filtering · holobiomicslab

    Use when after loading feature identification results (e.g., from OpenSwath or other DIA search engines) when you need to display only confident peptide precursors and their chromatograms.
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98. ▌
    Quality Control Merge Verification · holobiomicslab

    Use when after performing an inner or left join operation to combine a feature quantification table (from MZmine3) with sample metadata, and before proceeding to data cleanup, blank removal, batch correction, or statistical analyses.
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99. ▌
    Quality Control Metric Computation · holobiomicslab

    Use when after feature integration and imputation when you have QC-annotated LC-MS feature intensity data (CSV or data frame format) with replicate QC samples.
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100. ▌
     Quality Control Sample Designation · holobiomicslab

     Use when when importing a new batch of centroided mzML or mzXML LC-MS files into MetCohort, before any data alignment or feature detection is performed. At least one file must be designated as QC to enable ROA detection and alignment;
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