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HolobiomicsLab

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1. ▌
   Consensus Clustering Optimization · holobiomicslab

   Use when when you have a feature attribution matrix (e.g., microbe-metabolite interaction scores) from ensemble neural network training and need to group rows and columns into functionally coherent modules without pre-specifying cluster numbers.
   0 installs
2. ▌
   Constraint Based Model Validation · holobiomicslab

   Use when after gap-filling metabolic models in a community context when you need to verify that filled reactions maintain stoichiometric balance, that biomass production is feasible under community-level constraints, and that cross-member metabolic dependencies are satisfied.
   0 installs
3. ▌
   Count Matrix Statistical Modeling · holobiomicslab

   Use when after count matrix preprocessing (normalization, batch correction, low-count filtering) when you have a feature-by-sample count matrix and phenotype metadata, and you need to identify differentially expressed genes, miRNAs, isoforms, or other features across treatment groups or conditions.
   0 installs
4. ▌
   Cross Domain Metadata Integration · holobiomicslab

   Use when when you have conducted batch MS/MS searches across one or more domain-specific MASST tools and need to combine their hit scores, metadata annotations, and taxonomic lineages into a single coherent result set for comparative analysis or publication.
   0 installs
5. ▌
   Cross Organism Network Comparison · holobiomicslab

   Use when you have selected two organisms whose metabolic networks are available in KEGG and you need to quantitatively assess their structural and functional similarity to identify shared or divergent metabolic capabilities for comparative systems biology, drug target discovery, or evolutionary.
   0 installs
6. ▌
   Cross Validation Parameter Tuning · holobiomicslab

   Use when when building Cox-PH or Cox-nnet survival models from expression or metabolomic feature matrices paired with event/time vectors, and you need to select optimal regularization strength (alpha), cross-validation fold count (nfold), risk stratification method, and optimization strategy before.
   0 installs
7. ▌
   Data Type Constraint Verification · holobiomicslab

   Use when when ingesting or updating MassBank records in plain-text or structured format, and you need to verify that metadata fields (accession, name, formula, mass, spectrum peaks) comply with type definitions, presence requirements, and allowed value ranges.
   0 installs
8. ▌
   Deep Learning Survival Prediction · holobiomicslab

   Use when you have metabolomic or expression feature data, sample-level event indicators (e.
   0 installs
9. ▌
   Deployment Artifact Documentation · holobiomicslab

   Use when preparing a scientific application (such as a metabolite annotation tool) for deployment to a shared or production app server, particularly when the deployment requires external database access, Java library dependencies, and credential management.
   0 installs
10. ▌
    Dereplication Candidate Filtering · holobiomicslab

    Use when after spectral database dereplication (using Spectra) and compound database dereplication (using SIRIUS or MetFrag) have produced candidate annotations in CSV or JSON format.
    2 installs
11. ▌
    Dgl Molecular Graph Featurization · holobiomicslab

    Use when you have a set of SMILES or molecular structures and need to represent them as graph tensors for a Graphormer or other graph neural network model that predicts molecular properties (e.g., retention time, spectroscopic features).
    0 installs
12. ▌
    Docker Volume Mount Configuration · holobiomicslab

    Use when deploying the ipbhalle/metfragweb container and you need to supply custom MetFrag settings (ChemSpider tokens, proxy servers, local database connections) without modifying the container image.
    0 installs
13. ▌
    Executable Version String Parsing · holobiomicslab

    Use when your R package wraps a compiled .NET assembly or binary executable and you need to expose the version of that dependency to users at runtime for troubleshooting, validation, or documentation purposes.
    0 installs
14. ▌
    Fatty Acid Composition Generation · holobiomicslab

    Use when you need to systematically enumerate all possible lipid species within a defined analytical scope—specifically when you have specified one or more lipid classes (e.g., phosphatidylcholine, triacylglycerol) and fatty acid composition ranges (e.
    0 installs
15. ▌
    Feature Table Comparison Analysis · holobiomicslab

    Use when after running Paramounter's peak-height optimization on XCMS CentWave–extracted metabolomic features when you need to decide whether to accept the optimized threshold (maximizing true positives) or apply a higher threshold to reduce false positives and software crashes.
    0 installs
16. ▌
    Feedforward Network Configuration · holobiomicslab

    Use when when implementing multiple spectrum predictor baseline models (NEIMS, MassFormer, etc.) and you need to isolate the impact of encoder architecture on predictive performance.
    1 install
17. ▌
    File Format Conversion Validation · holobiomicslab

    Use when when you have raw mzML or mzXML mass spectrometry data files that need to be archived or transmitted with minimal storage footprint, and you must verify that the decompressed output exactly reproduces the original input at the byte level.
    3 installs
18. ▌
    File Format Detection And Routing · holobiomicslab

    Use when when you receive a mass spectrometry imaging dataset in unknown or mixed vendor formats and need to apply format-specific preprocessing before generating ion images.
    0 installs
19. ▌
    File Format Validation Proteomics · holobiomicslab

    Use when when raw MS files are uploaded to MSConnect via the Raw File Uploader and must be verified for compatibility with downstream processing tools (e.g., Proteomics_Data_Processor) before routing to the processing queue.
    2 installs
20. ▌
    File Io Error Handling Robustness · holobiomicslab

    Use when when designing or integrating a file parser for mass spectrometry formats (.raw Thermo RAW format, .mzml XML-based format) in a metabolomics processing pipeline, or when reading legacy or heterogeneous instrument output where file integrity cannot be guaranteed.
    0 installs
21. ▌
    Filter Module Toggle Verification · holobiomicslab

    Use when you need to confirm that a software API or tool correctly implements a boolean control over an optional filter module, particularly in contexts where filter activation state directly affects the set of predicted metabolites.
    0 installs
22. ▌
    Filter Threshold Parameterization · holobiomicslab

    Use when when expanding a compound set through multi-generation Pickaxe runs, use this skill if you want to retain compounds based on a similarity or property metric (e.
    0 installs
23. ▌
    Fold Change Frequency Aggregation · holobiomicslab

    Use when after performing univariate statistical testing (t-test or ANOVA via omu_summary or omu_anova) on metabolomics count data, use this skill when you need to summarize how many metabolites in each class showed significant increase or decrease (padj ≤ 0.05).
    0 installs
24. ▌
    Galaxy Installation Configuration · holobiomicslab

    Use when you have a Galaxy Master branch installation (or specific commit c429777c93680dcee449fe410f5360afbe673758) and need to add metabolomics tools from Galaxy-M.
    2 installs
25. ▌
    Galaxy Tool XML Option Formatting · holobiomicslab

    Use when when integrating a multi-backend metadata enrichment package (like MSMetaEnhancer) into Galaxy, and you need to expose all supported conversion options—such as SMILES, InChI, or CAS number conversions across multiple web services (CIR, CTS, PubChem, IDSM, BridgeDb) and compute backends.
    0 installs
26. ▌
    Gallery Benchmark Data Extraction · holobiomicslab

    Use when you have access to a computation-times table or performance log documenting rendering execution times for multiple visualization examples across different plotting backends (e.
    0 installs
27. ▌
    Gpu Accelerated Similarity Search · holobiomicslab

    Use when you have a large spectral library and many query spectra to search against it, and you need to identify both unmodified and open-modification peptides with strict false discovery rate control.
    2 installs
28. ▌
    Graph Representation Construction · holobiomicslab

    Use when you have KEGG metabolic data for one or more organisms and need to simultaneously analyze network topology and functional pathway organization—for example, when comparing metabolic capabilities between species for drug target discovery or when you need to expose both structural rewiring.
    2 installs
29. ▌
    Group Stratified Curve Generation · holobiomicslab

    Use when you have omics data with group labels (e.g., treatment vs. control, disease vs. healthy) and need to visualize how the cumulative distribution of a continuous variable (e.g., gene expression, abundance) differs between groups.
    2 installs
30. ▌
    Hash Based Deduplication Workflow · holobiomicslab

    Use when when processing open mass spectrometry library (OMSL) data that may contain duplicate spectral records (e.
    0 installs
31. ▌
    Hdf5 Cardinal Format Preservation · holobiomicslab

    Use when after performing isotopic correction, quantitation, or other pixel-level transformations on a feature-by-pixel intensity matrix imported from an imzML file via Cardinal's HDF5 layout.
    2 installs
32. ▌
    Hdf5 File Structure Specification · holobiomicslab

    Use when when exporting quantified MSI data (feature-by-pixel intensity matrices with associated ion m/z, lipid annotations, and pixel spatial coordinates) from LipidQMap and you need to produce a standards-compliant HDF5 container that can be read by Cardinal and other MSI analysis tools.
    0 installs
33. ▌
    Histogram Bin Width Configuration · holobiomicslab

    Use when you have uploaded a numeric column (e.g., H/C ratio, O/C ratio, or other derived properties from high-resolution mass spectrometry) and you are generating a histogram in Punc'data's Canvas tab.
    0 installs
34. ▌
    Identifier Mapping Implementation · holobiomicslab

    Use when when you have lipid names or abbreviations sourced from multiple databases (HMDB, LIPID MAPS, LipidHome, RefMet, SwissLipids) or software tools (LipidSearch, MS-DIAL, MZmine2, LipidBlast, etc.) and need to normalize them into a single canonical representation to enable data integration.
    1 install
35. ▌
    Inchikey Identifier Normalization · holobiomicslab

    Use when gNPS has stopped supplying ClassyFire ontology information for spectral library matches (as of the ConCISE documentation snapshot) and you need to manually retrieve chemical classifications.
    0 installs
36. ▌
    Ion Formula Matrix Classification · holobiomicslab

    Use when you have peak data from MSI experiments (stored as .zip peak matrix files) where matrix ions (e.g., silver adducts in AgLDI-MSI) dominate the spectrum and obscure analyte signals.
    0 installs
37. ▌
    Ion Mobility Class Stratification · holobiomicslab

    Use when you have TWIM-MS experimental data with assigned biomolecular class labels (e.g., peptides, lipids, carbohydrates) and arrival time measurements, and you need to compute CCS values conditioned on class membership.
    0 installs
38. ▌
    JSON Structured Report Generation · holobiomicslab

    Use when after Mass2Motif annotation candidates have been ranked and filtered by similarity score (using Spec2Vec embeddings queried against MotifDB), you need to serialize the ranked results into a standardized, hierarchical format that preserves confidence metadata and enables programmatic access.
    0 installs
39. ▌
    Knn Imputation Quality Assessment · holobiomicslab

    Use when after deciding to use KNN imputation on a metabolomic assay matrix with missing values, but before proceeding to normalization and statistical testing. Trigger conditions include: (1) your metabolomic dataset contains metabolites with varying degrees of missingness across samples;
    0 installs
40. ▌
    Large Scale Database Construction · holobiomicslab

    Use when you have a collection of molecular structures (as SMILES or SDF files) and need to generate pre-computed CCS values for fast retrieval in downstream mass spectrometry workflows.
    2 installs
41. ▌
    Lipid Concentration Normalization · holobiomicslab

    Use when your lipidomics experiment includes spiked internal lipid standards with known absolute concentrations, and you have a data matrix of signal intensities (samples × lipids) from LipidSearch or LIQUID output.
    0 installs
42. ▌
    Lipid Feature Identifier Matching · holobiomicslab

    Use when you have an isotope-corrected or raw MSI dataset stored in HDF5 format following Cardinal::HDF5 conventions, a user-provided internal standard definition (sample identifier and/or feature name), and need to locate and extract the intensity row for that lipid before performing ratio-based.
    2 installs
43. ▌
    Lipid Metadata Annotation Mapping · holobiomicslab

    Use when when exporting in-memory generated spectra as MSP-format spectral libraries, you must first map each spectrum record to required MSP fields (NAME, PRECURSORMZ, SPECTRUM) and optional metadata annotations.
    0 installs
44. ▌
    Lipid Nomenclature Simplification · holobiomicslab

    Use when you have spatial metabolomics data with semicolon-delimited isomer name annotations (such as the 'all_IsomerNames' column in SpaMTP Seurat objects) and you need to reduce annotation complexity before pathway analysis, statistical testing, or visualization.
    2 installs
45. ▌
    Mass Spectrometry File Conversion · holobiomicslab

    Use when you have vendor raw mass spectrometry data files (.raw) from a commercial instrument and need to convert them to open formats (mzML for spectral data, imzML for imaging mass spectrometry) for compatibility with third-party analysis software or to meet open-data standards.
    0 installs
46. ▌
    Mass Spectrometry Peak Validation · holobiomicslab

    Use when after peak alignment across all spectra in an MSImagingExperiment using peakAlign(), when you need to reduce the feature set to high-confidence peaks by removing spurious or low-frequency detections.
    0 installs
47. ▌
    Mass Trace Separation By Grouping · holobiomicslab

    Use when your pandas DataFrame contains mass spectrometry data with retention time (rt) and intensity columns AND a column representing different mass-to-charge (m/z) values or ion identifiers. This is particularly relevant when generating chromatogram plots from data with multiple mass traces (e.
    2 installs
48. ▌
    Metabolic Function Classification · holobiomicslab

    Use when when you have reconstructed metabolic networks from two or more organisms in KEGG and need to compare them not only in terms of reaction topology but also in terms of which metabolic functions (e.g., glycolysis, citric acid cycle) are present and how they differ.
    0 installs
49. ▌
    Metabolite Class Subset Filtering · holobiomicslab

    Use when when you have an omu_summary output dataframe with Class metadata and adjusted p-values (padj), and you need to focus downstream analysis (e.
    0 installs
50. ▌
    Metabolomics Data Matrix Handling · holobiomicslab

    Use when when you have raw metabolomics peak intensities or concentrations and accompanying sample metadata (batch, run order, sample type, factors of interest) and need to organize them into the featuredata, sampledata, and metabolitedata dataframes that NormalizeMets functions expect.
    0 installs
51. ▌
    Metabolomics Data Quality Control · holobiomicslab

    Use when after loading raw metabolomics data (e.g., from Metabolon, Nightingale, Olink, or SomaLogic platforms) into a Metaboprep object and before statistical analysis or modeling.
    0 installs
52. ▌
    Metabolomics Parameter Extraction · holobiomicslab

    Use when you have raw untargeted metabolomics data in mzML, mzXML, or CDF format from qTOF, Orbitrap, or FTICR mass analyzers, at least 3 samples, a sample metadata spreadsheet linking filenames to experimental factors, and need to generate optimized processing parameters for XCMS or MZmine2.
    0 installs
53. ▌
    Missing Data Mechanism Assessment · holobiomicslab

    Use when when you have a filtered metabolite abundance matrix with remaining missing values after feature-level filtering (e.g., removal of metabolites with >80% missingness), and you need to decide whether missingness is concentrated in specific features or sample pairs, or distributed randomly.
    0 installs
54. ▌
    Missing Value Imputation Strategy · holobiomicslab

    Use when your feature intensity table (samples × compounds) contains NA values and you intend to apply log transformation or scaling-based normalization. Specifically, apply this skill when the transf_data function is invoked with missing_replace=TRUE, before any log transformation or scaling step.
    0 installs
55. ▌
    Model Generalizability Evaluation · holobiomicslab

    Use when you have a pre-trained or newly retrained graph neural network for collision cross section prediction and need to measure whether its performance generalizes across different molecular datasets (e.g., training on METLIN but evaluating on CCSBase).
    2 installs
56. ▌
    Molecular Conformer Preprocessing · holobiomicslab

    Use when you have a set of molecular SMILES strings and need to prepare them as inputs to a deep-learning CCS prediction model.
    0 installs
57. ▌
    Molecular Fingerprint Calculation · holobiomicslab

    Use when you have a collection of small molecules in standardized format (SMILES or SDF) that require quantitative chemical feature representation for machine learning or comparative analysis.
    0 installs
58. ▌
    Molecular Representation Learning · holobiomicslab

    Use when when you have a collection of molecules with known property labels (e.g., retention times on a chromatographic column) and need to predict those properties on new compounds.
    2 installs
59. ▌
    Molecular Structure Parsing Rdkit · holobiomicslab

    Use when you have raw molecular structures in SMILES or SDF format from a chemical database (e.
    1 install
60. ▌
    Msi Array Data Structure Handling · holobiomicslab

    Use when you have imported raw imzML or Analyze 7.5 imaging data and need to represent it as a preprocessed spectral array before applying statistical methods (PCA, clustering, classification).
    0 installs
61. ▌
    Msi Metadata Curation And Storage · holobiomicslab

    Use when after generating a 3D pixel array (shape n+1, y, x) from raw line-scan MSI data via MSIGen's get_image_data() call, curate and validate the accompanying JSON metadata file before visualization or downstream analysis.
    0 installs
62. ▌
    Multi Omics Latent Space Learning · holobiomicslab

    Use when you have preprocessed and jointly normalized ST and SM data from the same sample(s) aligned to a common spatial resolution (via joint_adata_sm_st and normalize_total_joint_adata_sm_st), and you need to discover shared latent structure across modalities to identify co-localized spatial.
    0 installs
63. ▌
    Natural Product Model Application · holobiomicslab

    Use when you have (1) a collection of natural product or drug candidate molecules in SMILES format, (2) a downstream task (classification at Class/Superclass/Pathway levels, bioactivity regression, or virtual screening ranking), (3) access to pre-trained NaFM weights, and (4) a need to leverage.
    0 installs
64. ▌
    Noise Estimation Snr Thresholding · holobiomicslab

    Use when after normalizing, smoothing, and baseline-reducing mass spectra via normalize(), smooth(), and reduceBaseline(), when you need to distinguish true peaks from noise-induced artifacts.
    0 installs
65. ▌
    Online Mode Environment Detection · holobiomicslab

    Use when when deploying an OpenMS streamlit application that must support both local development (offline mode with multiprocessing) and production cloud/HPC environments (online mode with Redis + RQ task queue), and you need to transparently route workflow job submissions to the correct backend.
    0 installs
66. ▌
    Outlier Sample Identification Pca · holobiomicslab

    Use when after normalizing and log-transforming a LipidomicsExperiment object, when you need to detect samples with aberrant lipid profiles before differential expression or multivariate analysis.
    0 installs
67. ▌
    P Value Combination Fisher Method · holobiomicslab

    Use when when you have tabulated p-values and study sample sizes (N) from multiple independent metabolomics studies measuring the same compounds or metabolites, and you need to compute a single meta-analytic p-value that reflects both statistical significance and study weight.
    0 installs
68. ▌
    Package Installation Verification · holobiomicslab

    Use when after installing ChemDistiller or similar Python-based command-line analysis packages, to confirm the package is properly installed in the Python environment and the primary entry point script is accessible and executable.
    0 installs
69. ▌
    Peak Area Intensity Normalization · holobiomicslab

    Use when you have a targeted metabolomics peak area intensity table (samples in rows, compounds in columns) with assigned internal standards and you need to prepare data for quantification via regression models or statistical testing.
    0 installs
70. ▌
    Polarity Based Compound Filtering · holobiomicslab

    Use when you have a multi-polarity compound target list (e.g., a .xlsx file with a polarity or ionization mode column indicating positive or negative ESI mode) and you are about to perform targeted peak detection in a single LC–MS acquisition mode (e.g., positive-ion mode only).
    0 installs
71. ▌
    Pre Post Normalisation Comparison · holobiomicslab

    Use when after completing a hierarchical batch normalisation workflow (e.g., hRUV with intra-batch loess smoothing and inter-batch RUV-III correction) to verify that normalisation has eliminated run-order signal drift and batch-specific effects visible in raw or imputed assays.
    0 installs
72. ▌
    Python Data Structure Engineering · holobiomicslab

    Use when you have raw mass spectrometry quantification tables (feature abundance matrices), sample metadata tables, and spectral data files (e.g., from the omsw_pleurotus dataset) that must be ingested into the msFeaST pipeline;
    1 install
73. ▌
    Python Job Metadata Serialization · holobiomicslab

    Use when implementing online task queue deployments (RQ + Redis) where job execution may outlive the originating web session, or where workers may restart unexpectedly.
    0 installs
74. ▌
    Qm Output Parsing And Aggregation · holobiomicslab

    Use when you have completed parallel QUICK quantum calculations on multiple conformers filtered by ASE-ANI and need to extract electronic properties from the output logs and consolidate them into a single structured table for use in CCS calculations or metabolite annotation workflows.
    2 installs
75. ▌
    R Package Parameter Configuration · holobiomicslab

    Use when when preparing to preprocess Salmon-derived count matrices or other omics abundance data, and you need to specify multiple configurable options (e.
    0 installs
76. ▌
    R Package Workflow Implementation · holobiomicslab

    Use when you have raw unnormalized metabolomics intensity data organized by batch and sample type (QC vs. biological), and you need to remove systematic variation (drift, batch effects) while preserving biological signal.
    2 installs
77. ▌
    R Wrapper Function Implementation · holobiomicslab

    Use when when you have multiple imputation methods with different function signatures and parameter conventions that need to be applied to the same input data matrix, and you want to allow users or downstream code to switch between methods via a single method argument without rewriting calling code.
    0 installs
78. ▌
    Ranked Statistic List Preparation · holobiomicslab

    Use when after completing differential analysis (e.g., via run_de()) to generate p-values and log2 fold changes, and before executing fgsea-based MetSEA enrichment.
    1 install
79. ▌
    Rare Variant Integration Analysis · holobiomicslab

    Use when when analyzing rare-variant associations where sample sizes are modest, individual-variant tests lack power, or you need to aggregate signal across multiple rare variants within a biological pathway.
    2 installs
80. ▌
    Record Sorting By Multiple Fields · holobiomicslab

    Use when when applying str or matrix directives to JSON table data, and you need deterministic ordering of records before building output values—e.
    0 installs
81. ▌
    Regression Performance Evaluation · holobiomicslab

    Use when after training or fine-tuning a retention time prediction model on a source chromatographic method (e.g., SMRT dataset) and you need to verify prediction accuracy on a held-out test set or on a target chromatographic method from a different dataset (e.g., PredRet).
    2 installs
82. ▌
    Regulatory Relationship Inference · holobiomicslab

    Use when you have matched multiomics measurements (CNV, mutations, DNA methylation, histone PTMs, coding/noncoding transcripts, miRNA, lncRNA, proteomics, phosphoproteomics) across a cohort of cell lines or samples and want to identify which upstream omics features predict metabolite abundance.
    0 installs
83. ▌
    Retention Time Direction Matching · holobiomicslab

    Use when after componentization of parent and TP features with generateComponents(algorithm='tp'), when structural formula or compound annotations are available and you wish to prioritize TP candidates whose retention time behavior aligns with expected electronegativity, polarity, or hydrophobicity.
    0 installs
84. ▌
    Run Order Batch Effect Correction · holobiomicslab

    Use when metabolomics featuredata exhibits run-order-dependent signal drift, matrix effects, or batch effects that correlate with the order in which samples were analyzed.
    1 install
85. ▌
    Sample Group Metadata Association · holobiomicslab

    Use when you have a preprocessed count matrix (genes, miRNAs, isoforms, proteins, or lipids) and need to prepare it for differential expression analysis by linking sample identifiers to their experimental group assignments.
    0 installs
86. ▌
    Savitzky Golay Filter Application · holobiomicslab

    Use when apply Savitzky-Golay smoothing when your mass spectra contain significant noise but you need to preserve sharp peaks and spectral fine structure (e.g., isotope patterns, peak asymmetry).
    2 installs
87. ▌
    Shiny UI Component Implementation · holobiomicslab

    Use when you have an existing R package with statistical or data-processing functions and need to expose its functionality through an interactive web interface where end users (non-R programmers) can upload datasets, configure analysis parameters (e.
    0 installs
88. ▌
    Spatial Spectral Array Processing · holobiomicslab

    Use when you have preprocessed MSImagingArrays data (after normalization, smoothing, and baseline reduction) and need to detect peaks consistently across all spectra in an imaging experiment, create reference peak positions from a representative subset, and filter by signal-to-noise ratio and.
    0 installs
89. ▌
    Spectral Library Match Assignment · holobiomicslab

    Use when you have a set of candidate molecular structures from in silico fragmentation (e.
    0 installs
90. ▌
    Spectrum Grouping And Aggregation · holobiomicslab

    Use when you have loaded raw PSM search results from a proteomics search engine (e.g., MaxQuant, MSGFPlus, Sage) and need to prepare them for multi-rank rescoring in MS²Rescore.
    0 installs
91. ▌
    Statistical Sub Cluster Detection · holobiomicslab

    Use when you have a collection of Biosynthetic Gene Clusters that have been tokenised into Pfam domain and subPfam sequences and filtered for redundancy, and you seek to identify statistically significant groupings of genes that co-occur across multiple BGCs—particularly when downstream linking to.
    0 installs
92. ▌
    Statistical Test Dispatch Routing · holobiomicslab

    Use when after data preprocessing, quality control, and batch effect correction have produced a validated peak intensity matrix (feature table: samples × peaks) with associated sample metadata (phenotype, grouping, or class labels).
    0 installs
93. ▌
    Sub Cluster Assignment Extraction · holobiomicslab

    Use when after PRESTO-TOP topic modelling has been run on redundancy-filtered tokenised BGCs and raw topic assignments have been generated.
    0 installs
94. ▌
    Test Suite Execution Verification · holobiomicslab

    Use when when you have cloned or obtained a Python package repository and need to confirm that the codebase's tests pass before integration, contribution, or deployment. Particularly relevant when the repository advertises a Tests badge linked to a CI/CD workflow (e.
    2 installs
95. ▌
    Third Party Processor Integration · holobiomicslab

    Use when when you have raw MS files (e.g., .raw, vendor-specific formats) stored in a centralized repository and need to invoke a third-party proteomics analysis tool—such as a mass spectrometry feature detector or quantification engine—without manually managing file transfers or output.
    0 installs
96. ▌
    Treatment Group Comparison Design · holobiomicslab

    Use when you have paired metabolomics count data and metadata with at least two treatment groups (e.g., Strep vs Mock), a clear Factor column identifying group membership, and a research question about which metabolites differ significantly in abundance between treatments.
    0 installs
97. ▌
    Twim Instrument Offset Correction · holobiomicslab

    Use when you have raw TWIM-MS data with arrival times (detector timestamps) rather than drift times, and you need to calibrate collision cross section values. TWIM platforms inherently record arrival time, not drift time, so this correction must precede CCS calibration workflows.
    0 installs
98. ▌
    Ubuntu Package Inventory Analysis · holobiomicslab

    Use when when you have a Ubuntu-based software package (e.g., MetumpX) that advertises bundling a specific number of tools (~89) but the individual tool names, versions, installation sources, and installation methods are not enumerated in the README or primary documentation.
    0 installs
99. ▌
    Unit Test Design For File Parsing · holobiomicslab

    Use when when implementing or extending file format parsers in a spectral data pipeline, you need unit tests to ensure that format-specific parsers correctly instantiate spectrum objects with expected m/z arrays, intensity arrays, and metadata attributes before releasing to users or integrating.
    2 installs
100. ▌
     Bioconductor Package Operation · holobiomicslab

     Use when you have transcript-level quantification files (quant.gz, h5, or similar) from a known upstream quantifier (salmon, kallisto, sailfish, oarfish) and need to import them into R as matrices for differential expression analysis with edgeR, DESeq2, or limma-voom.
     0 installs