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HolobiomicsLab

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1. ▌
   Metabolic Network Edge Construction · holobiomicslab

   Use when when building a comprehensive chemical knowledge base for mass spectrometry formula assignment, particularly when you need to link chemical formulae across heterogeneous repositories (HMDB, ChEMBL, PubChem) and connect them through known metabolic transformations to improve annotation.
   0 installs
2. ▌
   Metabolic Network Topology Encoding · holobiomicslab

   Use when when you have reconstructed metabolic networks for one or more organisms and need to represent them in a way that preserves both the graph topology (connectivity structure) and the metabolic function annotations (pathway membership and enzymatic roles) for subsequent cross-organism.
   0 installs
3. ▌
   Metabolite False Positive Filtering · holobiomicslab

   Use when you have ion-mobility mass spectrometry metabolomics data with putative metabolite identifications (e.g., from database matching) and want to reduce false positives by cross-validating compound identities against machine-learned CCS predictions.
   0 installs
4. ▌
   Metabolite Identifier Cross Mapping · holobiomicslab

   Use when when you have metabolite identifiers from one or more metabolome databases and need to resolve them to equivalent identifiers in other databases, or when standardizing metabolite representation across multi-source metabolomic datasets where compounds may be annotated using different.
   2 installs
5. ▌
   Metabolite Identifier Normalization · holobiomicslab

   Use when your metabolomics dataset contains compound identifiers in mixed formats (chemical names, InChI strings, InChIKey hashes, or SMILES notation) and you need a single canonical identifier to enable meta-analysis across multiple studies or to avoid counting the same metabolite twice under.
   0 installs
6. ▌
   Metabolite Missing Value Imputation · holobiomicslab

   Use when metabolite assay tables contain missing values (NAs) that exceed detection or instrument runtime limits, AND you have retained metabolites with ≥60% non-missing data (i.e., ≤40% missingness).
   0 installs
7. ▌
   Metabolomic Data Quality Assessment · holobiomicslab

   Use when when you have raw metabolomics data with missing values in metabolite columns and need to prepare the dataset for downstream statistical analysis (linear mixed models, ANOVA, dimensionality reduction, or prediction models).
   0 installs
8. ▌
   Metabolomic Peak Quality Assessment · holobiomicslab

   Use when after peak detection in untargeted LC/HRMS workflows, when you have a list of candidate peaks with signal intensity profiles and need to filter them according to data quality thresholds (signal-to-noise ratio, peak width, baseline separation, and isotopic pairing consistency) before.
   0 installs
9. ▌
   Metadata Structure Field Enrichment · holobiomicslab

   Use when a metadata table contains compound names and identifiers but lacks structural data (SMILES, InChI, or molecular formula). The compounds are publicly available in PubChem and can be reliably identified by their chemical names. Use this skill before performing structure-dependent analyses (e.
   0 installs
10. ▌
    Model Weight Loading And Deployment · holobiomicslab

    Use when you have a pre-trained MSGO model checkpoint (PFAS or lipid variant) and need to evaluate it against a real mass spectrometry dataset (300+ real spectra, LC–QTOF, or custom CSV) to generate predicted molecular structures and compare against ground truth or baseline results.
    0 installs
11. ▌
    Molecular Descriptor Interpretation · holobiomicslab

    Use when you have a collection of molecules represented as CSV or EXCEL files containing computed molecular descriptors (e.g., physicochemical properties, structural features) and you need to predict whether each molecule will taste bitter.
    0 installs
12. ▌
    Molecular Formula Search Assignment · holobiomicslab

    Use when you have a recalibrated FT-ICR mass spectrum (Bruker .d format or equivalent) with detected, noise-thresholded peaks and need to assign chemical formulas to each peak. This is particularly relevant when analyzing samples with unknown composition (e.
    0 installs
13. ▌
    Molecular Structure Tensor Encoding · holobiomicslab

    Use when when you have raw molecular structure representations (SMILES strings, InChI notation, or chemical formulas) and need to feed them into a neural spectrum prediction model like SCARF or ICEBERG. Apply this skill before any forward inference pass through a pre-trained spectrum predictor.
    0 installs
14. ▌
    Multi Constraint Metabolic Modeling · holobiomicslab

    Use when you have metabolic models for multiple biological samples and need to distinguish between samples based on their metabolic phenotype, but single constraints (e.g., gene expression alone or nutrient availability alone) fail to segregate them adequately.
    0 installs
15. ▌
    Multimodal Feature Tensor Alignment · holobiomicslab

    Use when when you have molecule IDs converted to multiple independent feature modalities (graph-based node/edge tensors from RDKit, Morgan fingerprints, and computed physicochemical descriptors) and need to combine them into a single structured tensor representation for multimodal model training.
    2 installs
16. ▌
    Network Topology Metric Computation · holobiomicslab

    Use when after constructing or loading a network object (from adjacency matrix, edge list, or correlation output) and needing to quantify structural properties—such as identifying hub nodes via degree centrality, assessing clustering via coefficient distributions, measuring network resilience via.
    2 installs
17. ▌
    Open Modification Spectrum Matching · holobiomicslab

    Use when when you have a query mass spectrum with unknown or unanticipated post-translational modifications and need to match it against an unmodified spectral library.
    0 installs
18. ▌
    P Value And Fold Change Computation · holobiomicslab

    Use when you have raw metabolomics data organized as a matrix with metabolites as rows and samples as columns, sample group labels (e.
    0 installs
19. ▌
    P Value Interpretation Metabolomics · holobiomicslab

    Use when after fitting repeated measures ANOVA models to long-format imputed metabolomics data with a grouping variable (e.g., treatment, disease state) and subject-level random effects.
    0 installs
20. ▌
    Pandas Dataframe Plotting Interface · holobiomicslab

    Use when you have mass spectrometry data (retention time, m/z, intensity, or mobility dimensions) already loaded into a Pandas DataFrame and need to produce publication-ready or exploratory visualizations. Use this when you want to leverage Pandas' native .
    0 installs
21. ▌
    Parent Product Relationship Mapping · holobiomicslab

    Use when you have predicted biotransformation products from BioTransformer's environmental microbial degradation module (or similar rule-based prediction engines) and need to construct traceable lineages showing which parent compound(s) produced which metabolite(s) and what reaction type(s).
    0 installs
22. ▌
    Pathway Level Sample Stratification · holobiomicslab

    Use when you have per-sample metabolite abundance data and a metabolite-to-pathway association table, and need to assign each sample a dysregulation score for each pathway to enable downstream pathway-level classification, feature selection, or survival analysis.
    2 installs
23. ▌
    Pathway Level Statistical Inference · holobiomicslab

    Use when when you have genotype data (variants grouped by pathway annotation) and quantitative or binary phenotype data, and you want to test whether a pathway as a whole is associated with the phenotype, rather than testing individual variants.
    0 installs
24. ▌
    Peak Annotation With Bounding Boxes · holobiomicslab

    Use when you have isolated reference peaks from training chromatograms (ground-truth, single compounds per sample) and need to create a diverse, labelled training set large enough to train a CNN peak detector.
    0 installs
25. ▌
    Peak Center Coordinate Localization · holobiomicslab

    Use when you have LC-HRMS profile mode data with candidate peak regions (local maxima) exported as standardized rt×mz two-dimensional areas, and you need to automatically predict the precise peak-center location (both rt and mz coordinates) rather than relying on manual inspection or simple.
    2 installs
26. ▌
    Peak Integration Quality Assessment · holobiomicslab

    Use when you have a metabolomic feature table (rows=features, columns=samples) with peak height and peak area measurements from chromatographic processing, and you suspect data quality issues such as misaligned features or erratic peak integration across your sample cohort.
    0 installs
27. ▌
    Peptide Sequence Annotation Mapping · holobiomicslab

    Use when you have PSM files from a proteomics search engine (e.g., MaxQuant, MSGFPlus, MS Amanda) and need to convert their native modification notation into HUPO-PSI ProForma v2 format before rescoring. Specifically, use it when: (1) search engines report modifications with custom labels (e.
    2 installs
28. ▌
    Pre Analytical Stability Assessment · holobiomicslab

    Use when you have identified a set of lipid or polar metabolite analytes to measure from blood samples and need to determine whether they will remain stable under your planned or actual pre-analytical handling conditions (time delays before/after centrifugation and processing temperatures).
    0 installs
29. ▌
    Prediction Ensemble Post Processing · holobiomicslab

    Use when you have retention order predictions from multiple trained ROASMI models (e.g., ROASMI_1 through ROASMI_5) for the same set of compounds and need to estimate prediction uncertainty to support small molecule identification.
    0 installs
30. ▌
    Pubchem Compound Database Retrieval · holobiomicslab

    Use when you need to supply candidate metabolite structures for mass spectrometry annotation when working within an integrative metabolomics data analysis workflow (such as MAGMa).
    0 installs
31. ▌
    Python Conda Environment Management · holobiomicslab

    Use when when setting up a multi-language data analysis pipeline that requires both R and Python components to coexist with exact version constraints, especially when deep learning (keras) and machine learning (caret, pROC) packages must share a common Python backend.
    0 installs
32. ▌
    Python Random Access Implementation · holobiomicslab

    Use when when you have an indexed gzip file (mzML.gz with internal index structure) and need to retrieve individual spectra or chromatograms by integer index without decompressing the entire file.
    2 installs
33. ▌
    Pytorch Model Checkpoint Management · holobiomicslab

    Use when you have a pretrained GNN-RT model trained on a reference molecular database and need to adapt it to predict LC retention times on a different in-house molecular dataset with potentially different chromatographic conditions or chemical space.
    0 installs
34. ▌
    Qc Biological Sample Stratification · holobiomicslab

    Use when after metabolomics data normalization when both QC (quality control) and biological samples have been used in the same normalization run.
    0 installs
35. ▌
    Qc Sample Integration Normalization · holobiomicslab

    Use when normalizing multi-batch metabolomics intensity matrices where QC samples are available alongside biological samples, and when you need to detect whether QC samples are representative of the biological population (i.e., whether they follow the same systematic drift).
    0 installs
36. ▌
    Ras Dependent Flux Boundary Setting · holobiomicslab

    Use when when you have a generic constraint-based metabolic model, cell-line-specific or sample-specific transcriptomics data (e.g., FPKM or RNA-seq), and need to generate cell-relative metabolic models that account for differential gene expression.
    0 installs
37. ▌
    Rdkit Molecular Property Extraction · holobiomicslab

    Use when when you have a set of compounds represented as SMILES strings and need to compute their molecular properties (neutral mass, adduct-adjusted masses, mordred descriptors) for comparison against experimental peaks, retention time predictions, or similarity-based filtering thresholds during.
    2 installs
38. ▌
    Regression Model Evaluation Metrics · holobiomicslab

    Use when after training a deep-learning regression model (e.g., for CCS prediction from voxel projected area features), evaluate it on held-out test data to report per-molecule predictions and aggregate performance metrics.
    2 installs
39. ▌
    REST API Query And Response Parsing · holobiomicslab

    Use when you have deployed a TensorFlow Serving instance (via docker-compose or equivalent) and need to verify that the model's input layer names ('input_2048' and 'input_4096') and output layer name ('output') match the expected schema before integrating the model into a classification pipeline or.
    2 installs
40. ▌
    Retention Time Alignment Evaluation · holobiomicslab

    Use 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.
    0 installs
41. ▌
    Retention Time Intensity Extraction · holobiomicslab

    Use 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.
    0 installs
42. ▌
    Root Developmental Tissue Profiling · holobiomicslab

    Use when you have CDF-format mass spectrometry imaging files from plant roots with accompanying MATLAB workspace files (.mat), and your research goal is to reproduce linear-axis intensity profiles, feature distributions, and spatial metrics reported in a prior publication (e.g., Sama et al. 2025).
    0 installs
43. ▌
    Sample Quality Assessment Using Pca · holobiomicslab

    Use when after loading and basic filtering of (un)targeted metabolomic data (sample/feature missingness, peak area filters) but before aggregation or statistical modeling.
    0 installs
44. ▌
    Script Reproducibility Verification · holobiomicslab

    Use when when you have access to a repository containing simulation scripts (e.g., Type I error and power simulation code) and need to verify that the published findings—specifically reported error rates or power estimates—can be independently regenerated by re-running the deposited code.
    2 installs
45. ▌
    Semantic Version Parsing Comparison · holobiomicslab

    Use when before executing a bioinformatics pipeline that depends on multiple R packages with strict version constraints (e.g., DaDIA, which requires R ≥4.0, XCMS ≥3.11.4, and metaMS =1.25.1).
    0 installs
46. ▌
    Sequence File Inventory Enumeration · holobiomicslab

    Use when when you maintain a repository with local sequence files and need to determine which sequences are not publicly available in NCBI GenBank/RefSeq databases—for example, to distinguish proprietary or supplementary sequence data from publicly registered entries, or to create an inventory.
    2 installs
47. ▌
    Sequence To Sequence Model Training · holobiomicslab

    Use when you have paired multimodal scientific data (e.
    0 installs
48. ▌
    Smiles Sdf Molecule Format Handling · holobiomicslab

    Use when when you have molecular structures in SMILES or SDF format that need to be passed to CyProduct for metabolite prediction, or when you need to switch between string-based and file-based molecular representations for compatibility with different CYP450 enzyme prediction workflows.
    0 installs
49. ▌
    Spatial Transcriptomics Integration · holobiomicslab

    Use when you have paired spatial transcriptomics and spatial metabolomics datasets from the same sample(s) that are at different spatial resolutions or coordinate systems, and you need to integrate them for joint analysis of cross-modal spatial patterns.
    0 installs
50. ▌
    Spectral Database Schema Validation · holobiomicslab

    Use when when you have compiled raw mass spectrometry transition data (precursor m/z, product m/z, intensity, retention time, compound IDs) from experiments or external sources, and need to prepare it for ingestion into the EISA-EXPOSOME R Shiny platform for suspect screening.
    0 installs
51. ▌
    Spectral Intensity Trace Extraction · holobiomicslab

    Use when you have a Thermo Fisher Orbitrap .raw file and need to recover the intensity profile of a specific m/z value or peptide across the LC separation dimension (chromatogram), particularly when calibrating retention times against internal standards (iRT peptides), performing quality control.
    0 installs
52. ▌
    Spectral Quality Metrics Extraction · holobiomicslab

    Use when you have multi-sample MS1 data (from Agilent, Thermo, Bruker, or mzML formats) and need to quantify ion-level quality attributes—such as signal consistency, noise characteristics, or chromatographic stability—to either flag outlier samples or validate data fitness for downstream.
    2 installs
53. ▌
    Streamlit Session State Integration · holobiomicslab

    Use when when building a Streamlit web application that must coordinate stateful workflow execution across multiple reruns triggered by user interactions (e.
    0 installs
54. ▌
    Structured Data Matrix Construction · holobiomicslab

    Use when you have raw LipidSearch or LIQUID output files (CSV or TSV format) containing lipid identifiers and quantification columns (relative intensity or area values), and need to construct a clean, analyzable data matrix with consistent lipid nomenclature and no missing values in critical fields.
    2 installs
55. ▌
    Tensorflow Serving Layer Inspection · holobiomicslab

    Use when after deploying a TensorFlow model via TensorFlow Serving (e.
    0 installs
56. ▌
    Test Suite Execution And Validation · holobiomicslab

    Use when when you have cloned or obtained a Python package repository and need to verify that the package can be installed from source and that its test suite passes without errors.
    0 installs
57. ▌
    Unknown Sample Reference Comparison · holobiomicslab

    Use when you have a preprocessed unknown sample spectrum (m/z peaks and intensities) from high-throughput mass spectrometry (DI-MS, ASAP-MS, or ambient ionization methods) and need to identify the species or authenticate a sample against a curated reference database of known spectra.
    2 installs
58. ▌
    Web API Service Integration Mapping · holobiomicslab

    Use when you need to support multiple external services (CIR, CTS, PubChem, IDSM, BridgeDb, RDKit) for chemical identifier conversions (.
    0 installs
59. ▌
    Within Subject Correlation Modeling · holobiomicslab

    Use when your metabolomics dataset is in long format with repeated measurements per subject (id), a grouping variable (e.g., disease status or treatment arm), and metabolite abundances measured across time or visits.
    0 installs
60. ▌
    Gnn Spectral Property Prediction Workflow · holobiomicslab bundle

    Use when you want to train or apply a graph neural network over molecular graphs to predict a structure-dependent property — retention time, collision cross section (CCS), or an MS2 spectrum — and use that predicted property to filter or re-rank candidate structures for untargeted metabolomics annotation: build RDKit/PyTorch-Geometric molecular graphs from SMILES, design and train a GNN against a labelled property dataset, run inference to predict the property for candidate structures, and rescore a candidate pool by comparing predicted vs observed property values.
    0 installs
61. ▌
    Spec2vec Ml Embedding Annotation Workflow · holobiomicslab bundle

    Use when you want to annotate untargeted MS2 spectra with a machine-learned spectral embedding instead of raw cosine scoring — convert spectra into peak/neutral-loss "documents", train or load a Spec2Vec (Word2Vec-style) embedding model on a reference corpus, embed query spectra into that learned vector space, and retrieve/annotate nearest library neighbours by embedding similarity, as a deep-learning-adjacent second pass beyond modified-cosine matching.
    2 installs
62. ▌
    Stable Isotope Tracing Fluxomics Workflow · holobiomicslab bundle

    Use when you have LC-MS data from a stable-isotope (e.g. 13C / 15N) tracing experiment and want labelling / flux information — detect features, extract per-feature isotopologue distributions, correct for natural isotope abundance, and compute mass-isotopomer distributions and fractional labelling enrichment across conditions or timepoints.
    0 installs
63. ▌
    Biological Sequence Read Mapping · holobiomicslab

    Use when you have raw FASTQ sequencing reads (single-end or paired-end) and a reference transcriptome FASTA file, and you need to determine which transcript(s) each read aligns to in order to quantify transcript abundance. This is the core mapping stage in a salmon quant workflow;
    0 installs
64. ▌
    Count Data Normalization Rna Seq · holobiomicslab

    Use when you have raw read count matrices from RNA-seq quantification (e.g., from featureCounts, HTSeq, Salmon, or kallisto) and need to prepare them for differential expression analysis.
    0 installs
65. ▌
    Dimensionality Reduction Via Pca · holobiomicslab

    Use when apply PCA when you have a log-normalized, scaled gene expression matrix from highly variable genes and need to reduce dimensionality before constructing k-nearest neighbor graphs or other manifold-learning steps.
    0 installs
66. ▌
    Spatial Gene Ranking Computation · holobiomicslab

    Use when when working with spatial transcriptomics datasets (e.g., Slide-seq v2, MERFISH) stored in AnnData format and you need to identify genes whose expression shows significant spatial patterns or enrichment within tissue regions.
    0 installs
67. ▌
    Adduct Ion Parent Ion Pairing Analysis · holobiomicslab

    Use when when you have binned mass spectrometry imaging peaks and want to understand which detected mass-to-charge ratios represent the same metabolite in different ionization states (parent vs. adduct form).
    0 installs
68. ▌
    Fragmentation Pattern Annotation Magma · holobiomicslab

    Use when you have a tandem MS/MS spectrum of a structurally modified compound and a known reference structure (SMILES), and you need to annotate which fragment ions correspond to specific bonds or atoms in the molecule.
    0 installs
69. ▌
    Metabolite Feature Table Normalization · holobiomicslab

    Use when you have selected a subset of ReDU public tandem MS files with GNPS chemical annotations (level 2 or 3 spectral library matches) and wish to explore sample relationships via principal component analysis.
    0 installs
70. ▌
    Multivariate Ordination Interpretation · holobiomicslab

    Use when you have a collection of tandem MS/MS samples (stored in MassIVE) with GNPS spectral library annotations (m/z, retention time, compound identity), and you want to explore whether samples cluster by shared chemical features without predefined class labels.
    0 installs
71. ▌
    Unit Test Fixture Design And Execution · holobiomicslab

    Use when when implementing or modifying a numerical compression/decompression component (e.g., Numpress for mass-spectrometry m/z and intensity arrays) and you need to verify that round-trip encoding and decoding preserves numerical fidelity.
    0 installs
72. ▌
    Automated Reaction Network Exploration · holobiomicslab

    Use when when you have a molecular geometry (XYZ format) and need to predict electron ionization (EI) mass spectrum fragmentation patterns by exhaustively sampling conformational space and reaction intermediates.
    0 installs
73. ▌
    Baseline Model Training And Evaluation · holobiomicslab

    Use when when you need to establish comparable performance baselines for a novel spectrum prediction model and require fair comparison across multiple baseline architectures. Trigger this skill when: (1) you have a new spectrum prediction approach (e.g., ICEBERG, SCARF) to benchmark;
    0 installs
74. ▌
    Chromatographic Peak Detection Wavelet · holobiomicslab

    Use when you have loaded raw LC-MS or direct-injection FTICR-MS data (in mzML or netCDF format) into an XCMSnExp object and need to identify individual chromatographic peaks before feature grouping.
    0 installs
75. ▌
    Data Type Classification Schema Design · holobiomicslab

    Use when building or auditing a multi-instrument MS data processing system that must route different chromatography modes (LC, GC), ion mobility, or imaging modalities (MALDI) to distinct processing workflows.
    0 installs
76. ▌
    Feature Group Refinement Multicriteria · holobiomicslab

    Use 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;
    0 installs
77. ▌
    Gcxgc Chromatogram Object Manipulation · holobiomicslab

    Use when you have raw GCxGC-MS data in NetCDF format that contains instrumental and chemical noise (baseline drift, high-frequency signal artifacts) and you need to prepare multiple preprocessed chromatogram objects for downstream multiway PCA or biomarker discovery.
    2 installs
78. ▌
    Image Based Feature Extraction Ms Maps · holobiomicslab

    Use when you have a two-dimensional MS map (m/z vs retention time) from GC–MS or LC–MS data and need to discriminate analytes and identify marker features without false positives from peak picking; particularly useful for untargeted metabolomics at ppb sensitivity (e.
    2 installs
79. ▌
    Lc Ms Feature Extraction And Alignment · holobiomicslab

    Use when you have centroid mzML files from LC-MS experiments (converted from Thermo .raw or other vendor formats) and need to identify and quantify individual chemical features across multiple samples.
    2 installs
80. ▌
    Lc Ms Feature Grouping And Compounding · holobiomicslab

    Use when after chromatographic peak detection on preprocessed LC-MS data, when you have hundreds or thousands of individual m/z × retention-time peaks and need to associate them into biologically meaningful feature groups.
    0 installs
81. ▌
    Low Resolution Compound Identification · holobiomicslab

    Use when you have low-resolution GC-MS data (e.g., ANDI NetCDF format) with detected peaks that lack high mass accuracy, and you need to assign compound identities using a combination of retention index (RI) calibration and mass spectral library matching.
    2 installs
82. ▌
    Mass Spectral Metadata Standardization · holobiomicslab

    Use when you have acquired EI or MS/MS spectral libraries from multiple public sources (NIST, RIKEN, MoNA, SWGDRUG, GNPS) with inconsistent metadata field layouts, missing or misplaced SMILES entries, undocumented retention indices, or mixed polarity modes, and you need to merge them into a single.
    0 installs
83. ▌
    Mass Spectrometry Network Construction · holobiomicslab

    Use when you have deconvolved GC-MS spectra (output from auto-deconvolution) and want to group similar spectra into clusters to discover spectral families, identify co-eluting compounds, or organize unknown metabolites by structural similarity.
    0 installs
84. ▌
    Metabolite Record Deduplication · holobiomicslab

    Use when you have extracted metabolite records from two or more public metabolomics databases (e.g., HMDB, MassBank, METLIN) and need to merge them into a single reference database.
    2 installs
85. ▌
    Metabolite Structure Annotation · holobiomicslab

    Use when you have chemical structures (as SMILES or molecular structure formats) of environmental compounds and need to predict their microbial metabolites and degradation pathways.
    0 installs
86. ▌
    Metabolite Structure Generation · holobiomicslab

    Use when you have a small-molecule structure (SMILES, MOL, or SDF format) and need to predict its metabolic fate in a specific biological context (mammalian phase I/II metabolism, human gut microbiota, or soil/aquatic microbial degradation).
    2 installs
87. ▌
    Metabolite Trend Classification · holobiomicslab

    Use when when you have compiled p-values and fold-changes from multiple metabolomics studies and need to assign a single trend label (up/down/none) to each metabolite for meta-analysis or cross-study comparison.
    1 install
88. ▌
    Metabolomics Data Normalization · holobiomicslab

    Use when you have raw metabolomics data (samples × metabolic features matrix) collected across multiple analytical batches or instrument runs, and you observe evidence of technical heterogeneity—such as systematic shifts in metabolite intensities between batches, missing or zero values, or visual.
    0 installs
89. ▌
    Metabolon Excel Format Handling · holobiomicslab

    Use when you have raw Metabolon Excel workbooks (metabolon_v1.1_example.xlsx or metabolon_v1.2_example.
    0 installs
90. ▌
    Microbe Compound Identification · holobiomicslab

    Use when you have collected MS/MS spectra from a microbial sample (pure culture, environmental isolate, or mixed community) and need to assign chemical identities to observed m/z features while simultaneously resolving which microbial taxa are likely producers of each metabolite.
    2 installs
91. ▌
    Module Integration Verification · holobiomicslab

    Use when after rewriting or refactoring a Python module (such as calculate_feature_overlap.py in a metabolomics pipeline) to improve performance, maintainability, or functionality, you need to confirm that the new implementation does not introduce regressions.
    0 installs
92. ▌
    Molecular Descriptor Generation · holobiomicslab

    Use when you have a collection of chemical structures (80,000+ molecules from sources like METLIN SMRT dataset) that need to be converted into numerical feature vectors for machine learning-based retention time (RT) prediction, or when you need to compare descriptor-only, fingerprint-only, and.
    2 installs
93. ▌
    Molecular Geometry Optimization · holobiomicslab

    Use when you have generated multiple 3D conformers (e.g., from RDKit's distance-geometry algorithm) of ionized adducts and need to relax them toward local minima before filtering with machine-learning potentials or quantum methods.
    2 installs
94. ▌
    Multi Batch Comparison Analysis · holobiomicslab

    Use when you have a SummarizedExperiment object containing both a raw/imputed assay (e.g., rawImpute) and a normalized assay (e.
    0 installs
95. ▌
    Multi Charge State Ccs Handling · holobiomicslab

    Use when your TWIM-MS dataset contains ions with multiple charge states (e.g., +1, +2, +3 for the same molecular species) and you need CCS values that correctly account for the relationship between drift time, m/z, and charge state.
    0 installs
96. ▌
    Multi Format Data Serialization · holobiomicslab

    Use when after completing quality control, batch normalization, and outlier assessment on a Metaboprep object, when you need to: (1) save processed data matrices and metadata in human-readable tab-delimited format for use in other statistical or visualization tools;
    2 installs
97. ▌
    Mzml To Imzml Format Conversion · holobiomicslab

    Use when you have mzML files generated from raw vendor mass spectrometry imaging data and need to create imzML output compatible with software like Cardinal MSI, METASPACE, M2aia, or SCiLS Lab.
    2 installs
98. ▌
    Nan Propagation In Derived Data · holobiomicslab

    Use when when constructing derived elemental ratio images via Calculator formula evaluation in pew², and input element channels contain NaN pixels (from thresholding, signal dropout, or instrumental noise).
    0 installs
99. ▌
    Ncbi Database Cross Referencing · holobiomicslab

    Use when you have a collection of sequence files (e.g., GenBank format files in a repository directory) and need to determine which ones lack corresponding entries in NCBI's GenBank or RefSeq databases.
    0 installs
100. ▌
     Nextflow Workflow Orchestration · holobiomicslab

     Use when when you need to coordinate multiple bioinformatics tools (quality control, alignment, quantification, normalization, batch correction) across diverse compute environments (HPC, cloud, local) while ensuring reproducibility and parameter traceability.
     2 installs