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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Metabolomics Batch Correction Evaluation · holobiomicslab

   Use when when you have log2-transformed metabolomics data with known batch assignments and biological groupings, and you need to validate that a batch correction method (such as CordBat) has successfully removed batch-driven variation without collapsing true group differences in metabolite.
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2. ▌
   Metabolomics Group Comparison Statistics · holobiomicslab

   Use when you have a metabolomics matrix with metabolites as rows and samples as columns, each sample labeled with one of two experimental group identifiers (e.
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3. ▌
   Metabolomics Library Generation Pipeline · holobiomicslab

   Use when when you have cloned or accessed the Reverse_metabolomics_library_generation repository and need to verify that the Nextflow workflow is properly configured, executable, and produces expected spectral library outputs.
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4. ▌
   Metabolomics Preprocessing Normalization · holobiomicslab

   Use when you have acquired raw SIMS (secondary ion mass spectrometry) metabolite images aligned with tissue regions and segmented single-cell masks, and you need to extract normalized metabolite intensity values per cell before performing cell-type assignment, VAE embedding, or protein–metabolite.
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5. ▌
   Missing Value Imputation Method Dispatch · holobiomicslab

   Use when you have a metabolomics data matrix with missing-not-at-random (MNAR) left-censored values and need to apply multiple imputation methods to the same data in a standardized way, compare their outputs, or integrate the imputation step into a larger pre-processing pipeline.
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6. ▌
   Molecular Formula Parsing And Validation · holobiomicslab

   Use when you have received a formula-assigned FT-ICR MS dataset (CSV or tab-delimited table containing molecular formulas and mass values) and need to convert those formula strings into quantified elemental compositions before computing molecular descriptors, diversity indices, or transformation.
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7. ▌
   Molecular Structure File Format Handling · holobiomicslab

   Use when when you have molecular structures in one format (e.g., SMILES strings in a spreadsheet or text file) but need to feed them to a tool that accepts a different format (e.g., CypReact requires .sdf or .csv with SMILES).
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8. ▌
   Multiassayexperiment Object Manipulation · holobiomicslab

   Use when when you have parsed metabolite measurements into a table (rows = metabolites, columns = samples) and have corresponding sample-level covariates (e.g., disease status, treatment group) and/or feature-level annotations (e.
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9. ▌
   Parametric Nonparametric Model Selection · holobiomicslab

   Use when you have preprocessed, log₂-scaled metabolomics data in CSV format (samples × features) with batch assignment labels and need to decide which batch effect correction model to apply.
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10. ▌
    Pixel Intensity Scaling And Thresholding · holobiomicslab

    Use when after normalizing an MSI pixel array to TIC or an internal standard, when the raw pixel intensity distribution spans multiple orders of magnitude and produces images with poor contrast or where extreme outlier intensities would wash out spatial detail.
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11. ▌
    Polymorphic Method Dispatch On Plot Kind · holobiomicslab

    Use when when building a plotting library that must support multiple visualization types (1D spectra, chromatograms, mobilograms, 2D peak maps) across heterogeneous rendering backends, and you want users to specify plot type via a single kind parameter rather than importing backend-specific classes.
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12. ▌
    Psm Spectrum Identifier Regex Extraction · holobiomicslab

    Use when when you have PSM identifications from a search engine (e.
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13. ▌
    Publication Figure Formatting And Export · holobiomicslab

    Use when after generating initial visualizations (volcano plots, heatmaps, box plots, or bar plots) of lipid expression data, apply this skill when figures must be submitted to journals, supplementary materials, or presentations and must meet publication-quality standards for axes labels, legends.
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14. ▌
    Python Environment Dependency Resolution · holobiomicslab

    Use when when you have cloned a Python project repository and need to set up a working environment with all required packages, or when requirements.txt exists but dependencies are not yet installed in your current Python environment.
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15. ▌
    Qt Application Compilation And Packaging · holobiomicslab

    Use when you have a Qt5-based C++ GUI application source tree (e.g., Maven GUI) that must be compiled and packaged for end-user distribution across macOS and Windows platforms, especially when automated builds are managed by CI/CD services (AppVeyor, Travis).
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16. ▌
    Quality Control Sample Ratio Calculation · holobiomicslab

    Use when you have preprocessed metabolomics data stored in a SummarizedExperiment object containing QC sample measurements, assigned internal standards for compounds, and evidence of batch effects.
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17. ▌
    R Data Frame Construction And Validation · holobiomicslab

    Use when when you have instrument-exported text files (e.g., Sciex MultiQuant txt format) containing QCpool sample measurements, metadata, and timestamps that need to be converted into a reproducible, schema-validated R object for metabolomics or lipidomics quality overview analysis.
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18. ▌
    Retention Time Normalization And Scoring · holobiomicslab

    Use when you have XCMS-aligned feature tables with retention time values and need to compute pairwise feature similarity.
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19. ▌
    Sampletype Phenotype Stratified Plotting · holobiomicslab

    Use when after loading and normalizing a LipidomicsExperiment object with logged Area measurements, when you need to assess whether clinical sample groups (e.
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20. ▌
    Screening Performance Metric Computation · holobiomicslab

    Use when after running inference with a pre-trained or fine-tuned NaFM model on a virtual screening dataset (compounds with known bioactivity labels or ground truth), compute screening-specific performance metrics to evaluate retrieval and ranking capability.
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21. ▌
    Sequence To Sequence Architecture Design · holobiomicslab

    Use when when you have encoder-produced fixed-size embeddings and need to generate variable-length discrete sequences (e.g., SMILES tokens, protein sequences, chemical formulas) as outputs.
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22. ▌
    Similarity Score Computation For Spectra · holobiomicslab

    Use when you have a preprocessed unknown sample spectrum (m/z peaks and intensities) and need to identify the most likely species or reference entries by scoring it against a database of known spectra.
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23. ▌
    Singular Value Decomposition Application · holobiomicslab

    Use when you have a metabolite intensity matrix (samples × metabolites, log₂-transformed and standardized) and pathway definitions (pathway IDs mapped to metabolite sets), and you need to score pathway activity across samples in a way that tolerates noise and missing peaks.
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24. ▌
    Spans Centering Procedure Implementation · holobiomicslab

    Use when normalizing peptide or protein-level quantification matrices in proteomics workflows and you need to center the data but lack domain knowledge to manually select among mean, median, geometric mean, or robust centering methods.
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25. ▌
    Spectral Library Annotation Augmentation · holobiomicslab

    Use when you have a GNPS DBResult file containing spectral library matches with InChIKey identifiers but lacking ClassyFire ontology columns (superclass, class, subclass), and you need to restore this taxonomic context for consensus classification or chemical ontology annotation workflows.
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26. ▌
    Spectral Peak Filtering By Mass Accuracy · holobiomicslab

    Use when after molecular formula assignment has been performed on FT-ICR MS peaks (e.g., by Formularity or CoreMS), and before calculating thermodynamic indices, compound class assignments, or statistical analysis.
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27. ▌
    Spectrum Filtering With Deletion Logging · holobiomicslab

    Use when processing heterogeneous mass spectrometry libraries (e.g., from OMSLs) where chemical identifiers are unevenly populated across records.
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28. ▌
    Sub Network Detection From Scored Graphs · holobiomicslab

    Use when you have a GLASSO-inferred sparse network graph and associated PCA scores (e.g., from prior dimension reduction of omics or imaging data), and you need to identify which nodes cluster together based on both their PCA score patterns and their connectivity in the graph.
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29. ▌
    Tomcat Application Server Initialization · holobiomicslab

    Use when when you need to deploy a Java web application packaged in a Tomcat Docker container to a specified HTTP endpoint, and must verify that the container starts successfully, the Tomcat server initializes, and the application becomes accessible at the mapped host port before proceeding with.
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30. ▌
    Transformation Network Topology Analysis · holobiomicslab

    Use when when you have pre-processed FT-ICR MS peak lists with assigned molecular formulas and wish to move beyond univariate chemical composition analysis to understand metabolic transformation pathways and hub metabolites.
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31. ▌
    U13c Labeled Standard Reference Matching · holobiomicslab

    Use when you have IM-MS measurements of samples spiked with U13C-labeled internal standards (e.g., fully labeled yeast extract) and need to assess whether measured CCS values systematically deviate from their true reference values.
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32. ▌
    Unit Test Design For Biochemical Filters · holobiomicslab

    Use when after implementing a custom Filter subclass (e.g., MetabolomicsFilter, TanimotoFilter) in minedatabase/filters.py, you must write unit tests to validate that _choose_cpds_to_filter correctly identifies compounds to retain/remove.
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33. ▌
    Validated Dataset Integrity Verification · holobiomicslab

    Use when you have received a validated dataset (e.g., interim/tables/4_analysed/platinum.tsv.
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34. ▌
    Gcms Deconvolution Identification Workflow · holobiomicslab bundle

    Use when you have GC-MS data (mzML / CDF, typically EI) and want deconvolved, retention-index-validated compound identifications — spectral deconvolution of co-eluting peaks, EI library matching, RI calibration, and differential analysis.
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35. ▌
    Adaptive Prior Distribution Selection · holobiomicslab

    Use when after running DESeq() and extracting raw results with results(), when you have log fold change estimates with high variance and wish to improve their precision.
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36. ▌
    Buffer Management And Flush Protocols · holobiomicslab

    Use when when quantifying or mapping RNA-seq reads with salmon quant using the --writeMappings (-z) flag, or in any streaming output scenario where record count discrepancies appear between reported totals (e.g., NumReads in quant.sf) and file contents (SAM record count).
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37. ▌
    Differential Gene Expression Analysis · holobiomicslab

    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 more treatment groups.
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38. ▌
    Gene Length Offset Matrix Computation · holobiomicslab

    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 usage across your experimental conditions.
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39. ▌
    K Nearest Neighbor Graph Construction · holobiomicslab

    Use when after PCA dimensionality reduction and scaling of normalized, log-transformed gene expression data, when you need to identify local cell neighborhoods (typically with k=15 neighbors) before applying clustering algorithms like Leiden or computing UMAP embeddings.
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40. ▌
    Pathway Activity Correlation Analysis · holobiomicslab

    Use when when you have run gene set enrichment analysis (e.
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41. ▌
    Pearson Correlation Analysis Genomics · holobiomicslab

    Use when when comparing transcript quantification outputs (NumReads counts, abundance estimates) from two mapper implementations (e.
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42. ▌
    Per Read Mapping Agreement Assessment · holobiomicslab

    Use when comparing mapping outputs from two different salmon versions or implementations (e.g., C++ 1.12.0 vs. Rust 2.0) to determine if observed differences in total mapped read counts are due to true algorithmic bugs, parameter defaults, or index format changes.
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43. ▌
    Rna Seq Read Mapping Parameter Tuning · holobiomicslab

    Use when when comparing two implementations of the same RNA-seq mapping algorithm on identical reference indices and read sets, if per-read mapping agreement is <99.8% or the overall mapping rate differs by >0.
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44. ▌
    Transcript Quantification Integration · holobiomicslab

    Use when you have transcript quantification output (TPM or raw counts) from a pseudo-aligner (Salmon or kallisto) and an ioe/ioi event definition file from SUPPA2's generateEvents step, and you need to calculate PSI values—the relative inclusion level of alternative splicing events—across multiple.
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45. ▌
    Mass Spectrometry File Inventory Management · holobiomicslab

    Use when you have uploaded MS/MS data to MassIVE with validated sample-information metadata and need to subset public files by sample attributes (organism, tissue type, extraction method, ionization source, pre-MS separation) to create reproducible, manageable cohorts for molecular networking.
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46. ▌
    Ondiskmsnexp Object Manipulation And Export · holobiomicslab

    Use when you have raw CE-MS data and need to (1) transform migration time values to effective mobility using two calibration markers (e.
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47. ▌
    Reaction Pathway Assignment And Propagation · holobiomicslab

    Use when you have detected and clustered unknown MS features from untargeted xenobiotic metabolomics data, computed fragmentation pattern similarity scores between features and reference spectra, and now need to systematically assign individual features to specific biotransformation reactions (e.
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48. ▌
    Recursive Propagation Algorithm Development · holobiomicslab

    Use when when you have constructed a two-layer metabolite annotation network (knowledge-driven and data-driven) and need to propagate initial seed annotations (e.
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49. ▌
    Xenobiotic Metabolite Annotation From Ms Ms · holobiomicslab

    Use when you have aligned MS/MS feature tables (e.g., from MSDial ver. 4.80) representing unknown metabolites suspected to be Phase I/II transformation products of xenobiotics, and you need to assign both chemical identity and biotransformation pathway context to each feature.
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50. ▌
    Baseline Method Comparison And Benchmarking · holobiomicslab

    Use when you have developed or adapted an analytical method (e.g., NPFimg for GC–MS marker identification) and need to demonstrate its reliability or improved performance over a widely-used reference method (e.g., XCMS). Apply this skill when you have access to both the same raw input data (e.
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51. ▌
    Chemical Metadata Retrieval And Aggregation · holobiomicslab

    Use when after raw GC-MS CSV input has been parsed into separate matrices (Component.RT, Base.Peak.MZ, Compound.Name, Match.Factor, Component.Area) and you need to enrich sample-level identifications with authoritative chemical properties.
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52. ▌
    Chemical Type Classification And Annotation · holobiomicslab

    Use when after identifying query chemicals from GC-MS data (via Match.
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53. ▌
    Data Structure Design For Spectral Searches · holobiomicslab

    Use when you have raw GC-MS output in CSV format with columns Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, and File.
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54. ▌
    Mass Spectrometry Column Polarity Filtering · holobiomicslab

    Use when you have a combined EI library (from multiple sources such as NIST, RIKEN, MoNA) and access to NIST RI database files (ri.dat and USER.
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55. ▌
    Mass Spectrometry Scoring Method Validation · holobiomicslab

    Use when you have high-resolution LC-MS data processed through both XCMS feature detection and RAMClustR clustering, and you need to verify the reliability of molecular weight assignments before downstream annotation or statistical analysis.
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56. ▌
    Metadata Field Extraction And Restructuring · holobiomicslab

    Use when reading mass spectral library files (particularly MoNA EI or MS2 libraries) where structural metadata like SMILES information is embedded in general-purpose fields (e.g., Comment field) rather than in the dedicated SMILES field expected by mspcompiler's downstream processing steps.
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57. ▌
    Spectral Peak Word Embedding Representation · holobiomicslab

    Use when when you have MS/MS spectra (LC-MS or equivalent positive ionization mode data) that you intend to embed using Word2Vec or similar distributional semantic models, or when you need to prepare spectral data for training similarity models that learn peak co-occurrence patterns rather than.
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58. ▌
    Adduct Form Prediction And Mass Calculation · holobiomicslab

    Use when you have a characterized lipid species (with defined class and fatty acid composition) and need to predict which adduct forms will ionize under your experimental ionization mode (positive or negative ESI), and you require accurate precursor m/z values for DDA method configuration or.
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59. ▌
    Adduct Formation Prediction For Metabolites · holobiomicslab

    Use when when you have unidentified LC/MS features (m/z, retention time, intensity) and need to disambiguate which metabolites they represent by accounting for the fact that observed m/z values may correspond to different adduct forms (e.
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60. ▌
    Annotation Benchmark Performance Evaluation · holobiomicslab

    Use when after running an end-to-end annotation workflow (matching, clustering, filtering, and prioritization) on untargeted LC-MS peak tables, when you have access to a curated reference dataset (df.Ref) containing validated peak assignments for the same biological sample.
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61. ▌
    Batch Effect Assessment Via Quality Metrics · holobiomicslab

    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 and matrix effects are acceptable for downstream reporting.
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62. ▌
    Box Cox Transformation Parameter Estimation · holobiomicslab

    Use when you have raw LC-MS feature-intensity tables (rows: samples, columns: metabolite features, values: raw intensities) with non-normal, skewed distributions and need to normalize them prior to statistical analysis.
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63. ▌
    Calibration Coefficient Accuracy Assessment · holobiomicslab

    Use when after applying deimos.calibration.tunemix() to positive-mode or negative-mode tune mix reference data (containing known CCS values across m/z range 118–1522), assess whether the single-field calibration model's r-squared coefficient meets the expected precision (typically ≥0.
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64. ▌
    Chromatogram Plot Generation Retention Time · holobiomicslab

    Use when you have mass spectrometry data loaded as a Pandas DataFrame with retention time and intensity columns, and you need to visualize the overall or mass-trace-specific signal intensity distribution across the chromatographic separation.
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65. ▌
    Chromatographic Peak Detection And Grouping · holobiomicslab

    Use when when you have processed LC-MS data through XCMS alignment but suspect misaligned features due to retention-time drift over long acquisition periods (>1 week) or large sample batches (hundreds of samples), or when peak-filling produces unexpectedly high coefficient-of-variation (CV > 0.
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66. ▌
    Classification Model Performance Evaluation · holobiomicslab

    Use when after fitting and optimizing a MB-PLS model on training data, apply this skill to the held-out test set (typically 10% of the original sample) to obtain unbiased performance estimates.
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67. ▌
    Confidence Score Thresholding In Proteomics · holobiomicslab

    Use when when loading search results from Data-Independent Acquisition (DIA) mass spectrometry workflows (e.g., output from OpenSwath or similar feature detection tools) and you need to restrict the analyte pool to those meeting a strict false-discovery rate (FDR) threshold.
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68. ▌
    Constraint Based Flux Sampling And Analysis · holobiomicslab

    Use when when you have constraint-based metabolic models for multiple samples or cell lines, and you want to determine whether integrating multiple omics constraint types (nutrient availability, extracellular metabolite ratios, gene expression) produces distinct and biologically meaningful.
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69. ▌
    Cross Database Structural Homology Matching · holobiomicslab

    Use when when you have antiSMASH-predicted BGCs and wish to link them to metabolomic data via structure prediction, but only BGCs with sufficient structural homology to characterized reference clusters will yield reliable predictions.
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70. ▌
    Cross Dataset Score Distribution Comparison · holobiomicslab

    Use when when you have applied multiple scoring functions (e.g., strain correlation and IOKR) to rank genomic-metabolomic (GCF-MF or BGC-spectrum) links and need to verify that: (1) standardisation produces zero mean and unit variance across all links;
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71. ▌
    Cross Language Data Format Interoperability · holobiomicslab

    Use when you have mass spectrometry data (LC–MS/MS, ion mobility, DIA) converted to MZA format and need to read or analyze it in multiple programming languages (Python and R), or share datasets with collaborators using different environments without requiring proprietary vendor libraries or format.
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72. ▌
    Data Driven Similarity Layer Implementation · holobiomicslab

    Use when you have untargeted metabolomics mass spectrometry data (MS2 spectra with m/z values and intensities) and an existing knowledge-driven metabolite network, and you need to enhance annotation accuracy and coverage by leveraging experimental similarity patterns rather than relying solely on.
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73. ▌
    Dda Fragmentation Strategy Parameterization · holobiomicslab

    Use when you have a virtual chemical mixture (MS1 peaks) and need to prototype a new DDA acquisition strategy before testing on real instrumentation. Use this skill when you want to compare how different parameter combinations (e.g., TopN=3 vs TopN=5, isolation_width=0.5 Da vs 1.
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74. ▌
    Entropy Based Spectral Distance Computation · holobiomicslab

    Use when when comparing two preprocessed MS/MS spectra for compound identification and you need higher accuracy than dot product similarity provides.
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75. ▌
    Feature Sub Group Refinement And Validation · holobiomicslab

    Use when after initial retention-time-based feature grouping (e.
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76. ▌
    Feature Table Annotation Table Construction · holobiomicslab

    Use when after feature extraction from XCMS or MS-Dial when you have a feature intensity table (samples × features), a feature info table with m/z and retention time measurements, and access to a reference compound database with known m/z, retention time, and compound metadata.
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77. ▌
    Feature Table Integration And Normalization · holobiomicslab

    Use when when you have MS1 feature tables from heterogeneous sources—e.g., XCMS peak detection output mixed with vendor software (MS-DIAL, MZmine2) results—and need to merge them into a single, format-normalized table for ISFrag analysis.
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78. ▌
    Filter Status Data Structure Interpretation · holobiomicslab

    Use when after applying a sequence of mpactr filters (filter_mispicked_ions, filter_group, filter_cv, filter_insource_ions) to an LC-MS/MS peak table in Progenesis or MS-DIAL format, call qc_summary() to obtain a structured report of per-ion filtering outcomes and use this skill to understand.
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79. ▌
    Gaussian Process Uncertainty Quantification · holobiomicslab

    Use when after collecting observed separation efficiency scores at sampled gradient conditions and you need to propose the next gradient to evaluate.
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80. ▌
    Graph Neural Network Encoding For Molecules · holobiomicslab

    Use when you have molecular structures (SMILES or SDF format) that need to be matched against MS/MS spectra, or you need to compute similarity between query spectra and a reference library of compounds.
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81. ▌
    Interactive Network Visualization Rendering · holobiomicslab

    Use when after structural clustering (isotopologue grouping, adduct detection, cross-assay linking) and correlation clustering of LC-MS features, when you need to inspect and communicate the topology of structural relationships—particularly when the number of features or link types is too dense for.
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82. ▌
    Ionization Polarity Selection And Filtering · holobiomicslab

    Use when loading raw mass spectrometry data (MGF, mzML, or msp format) into MS2LDA and you need to isolate spectra from a single ionization polarity.
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83. ▌
    Isotopic Signature Validation And Filtering · holobiomicslab

    Use when after isotope detection has enumerated C13 isotopologue patterns across m/z, drift time, and retention time dimensions, and you need to reduce false positives by retaining only well-populated isotopic signature clusters before annotation or export.
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84. ▌
    Latent Dirichlet Allocation Topic Inference · holobiomicslab

    Use when you have a preprocessed corpus of mass spectrometry spectra converted to bag-of-fragments format (with neutral losses extracted and noise filtered), and you seek to discover recurring fragmentation patterns or substructures that characterize multiple spectra without prior knowledge of the.
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85. ▌
    Mass Accuracy Collision Energy Optimization · holobiomicslab

    Use when you have defined a set of lipid targets (species, adducts, chain compositions) for PRM or MRM analysis and need to generate precursor-to-fragment transition rules that will maximize signal intensity and specificity on your mass spectrometer (Thermo QExactive HF, Agilent QTOF, or.
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86. ▌
    Mass Defect Filtering For Chemical Validity · holobiomicslab

    Use when after loading an MS-DIAL peak list (feature table with m/z, retention time, intensity, and sample assignments) when you need to remove non-organic or chemically implausible features.
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87. ▌
    Mass Spectrometry Method Cycle Verification · holobiomicslab

    Use when when you have a Thermo Fisher Scientific Orbitrap .raw file and need to confirm that a targeted acquisition method (e.g., PRM targeting a specific precursor m/z) is achieving uniform cycle timing.
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88. ▌
    Mass Spectrometry Scan Extraction By Target · holobiomicslab

    Use when you have raw LC-MS/MS chromatogram files in mzML/mzXML format (converted from Thermo, Waters, or Bruker instruments) acquired in DDA or targeted MS/MS mode, and you need to isolate specific MS1 precursors and their corresponding MS2 fragments based on known m/z values and optional.
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89. ▌
    Metabolite Annotation Confidence Assignment · holobiomicslab

    Use when you have a feature intensity table with feature metadata (m/z, retention time) extracted from XCMS or MS-Dial, and you want to cross-reference each feature against a known-compound database to assign standardized confidence levels.
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90. ▌
    Metabolite Annotation Taxonomic Integration · holobiomicslab

    Use when you have paired metabolomics data (MS/MS spectra and feature quantification) linked to organismal or tissue taxonomy, and you want to reduce false positive annotations and improve annotation rank by filtering candidate metabolites to those chemically plausible within the given taxon.
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91. ▌
    Metabolite Candidate Ranking Interpretation · holobiomicslab

    Use when after running annotateRC() on LC-MS AIF features, when you need to validate whether a feature's rank-1 annotation is reliable or when you suspect that structurally similar metabolites (e.
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92. ▌
    Metabolite Feature Filtering By Missingness · holobiomicslab

    Use when you have a raw metabolite abundance matrix (e.g., from MSPrep or another LC-MS/MS pipeline) with many features and samples, and you observe that a substantial fraction of metabolites are missing (NA or zero-valued) across replicates.
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93. ▌
    Metabolite Feature Matching Across Datasets · holobiomicslab

    Use when you have two independent LC-MS untargeted metabolomic feature tables (e.
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94. ▌
    Metabolite Identity Ground Truth Validation · holobiomicslab

    Use when after constructing candidate feature pair alignments and retention-time spline mappings in a multi-dataset LC-MS metabolomics integration workflow, when you have access to independent ground-truth annotations (e.
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95. ▌
    Metabolite Structure Annotation Integration · holobiomicslab

    Use when you have a set of candidate transformed structures generated by biotransformation rules (e.
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96. ▌
    Metabolomics Feature Integration Assessment · holobiomicslab

    Use when after XCMS peak picking and fillPeaks() when you have xcmsEIC and filled xcmsSet objects and need to systematically flag low-quality or unreliable peak integrations prior to statistical modeling or machine learning classification.
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97. ▌
    Missing Value Imputation Strategy Selection · holobiomicslab

    Use when after mark_nas() has replaced non-NA missing-value codes (e.g., 0, 1) with R's NA in the exprs matrix of a MetaboSet object, and you need to decide whether to apply random forest imputation, simple imputation strategies, or defer imputation.
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98. ▌
    Molecular Formula Isotopic Profile Matching · holobiomicslab

    Use when you have detected peaks from untargeted LC/HRMS analysis (via IDSL.IPA or equivalent peak picker) with m/z and retention time values, and you need to assign molecular formulas to those peaks.
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99. ▌
    Motif Pseudo Spectra Optimization Filtering · holobiomicslab

    Use when after LDA has converged and inferred Mass2Motifs from preprocessed mass spectrometry spectral data, when the raw motif-fragment distributions contain noise or low-confidence associations that obscure the dominant fragmentation patterns.
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100. ▌
     Ms2 Fingerprint Blank Contamination Removal · holobiomicslab

     Use when after aligning MS2 fingerprints across samples (generating a sample-by-feature occurrence matrix) and before applying visualization techniques (MDS/PCoA, TMAP, Heatmap) or statistical comparisons.
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