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HolobiomicsLab

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1. ▌
   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
2. ▌
   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.
   0 installs
3. ▌
   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
4. ▌
   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
5. ▌
   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
6. ▌
   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
7. ▌
   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
8. ▌
   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
9. ▌
   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
10. ▌
    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
11. ▌
    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
12. ▌
    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
13. ▌
    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
14. ▌
    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
15. ▌
    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
16. ▌
    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
17. ▌
    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
18. ▌
    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.
    0 installs
19. ▌
    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
20. ▌
    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.
    0 installs
21. ▌
    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
22. ▌
    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.
    0 installs
23. ▌
    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
24. ▌
    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
25. ▌
    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.
    0 installs
26. ▌
    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
27. ▌
    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).
    0 installs
28. ▌
    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.
    0 installs
29. ▌
    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
30. ▌
    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
31. ▌
    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.
    0 installs
32. ▌
    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
33. ▌
    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.
    0 installs
34. ▌
    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.
    0 installs
35. ▌
    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
36. ▌
    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
37. ▌
    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;
    0 installs
38. ▌
    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.
    0 installs
39. ▌
    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
40. ▌
    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
41. ▌
    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.
    0 installs
42. ▌
    Numeric Variable Range Analysis · holobiomicslab

    Use when you have loaded a numeric column (e.g., H/C ratio, O/C ratio, m/z value, or intensity) from a CSV file into Punc'data and need to render a histogram with appropriate bar spacing. The skill is triggered when the range of the column is small enough that default bin widths (1.
    0 installs
43. ▌
    Object Oriented Design Analysis · holobiomicslab

    Use when you need to understand or document the extensibility architecture of a modular OOP codebase—specifically when developers must identify which classes, interfaces, or modules to extend or improve, or when onboarding contributors to a project whose documentation does not explicitly expose its.
    0 installs
44. ▌
    Outlier Detection And Treatment · holobiomicslab

    Use when when you have a Metaboprep object with raw or batch-normalized metabolomics abundance data and need to detect samples that deviate significantly from the central distribution due to technical artifacts, processing errors, or biological extremes.
    0 installs
45. ▌
    Parameter Conditional Execution · holobiomicslab

    Use when when a post-processing step (such as dereplication) risks removing true positive signals due to overly strict thresholds, and you need the option to retain raw or unfiltered output without code branching.
    0 installs
46. ▌
    Pathway Robustness Benchmarking · holobiomicslab

    Use when when selecting a pathway analysis method for metabolomics peak data where noise and missing peaks are prevalent, or when validating that a chosen method performs consistently across realistic data quality variations.
    0 installs
47. ▌
    Peak Height Threshold Selection · holobiomicslab

    Use when when applying iterative peak detection (local-maximum or Gaussian-fit methods) to 1D extracted ion chromatograms (XICs), arrival time distributions (ATDs), or MS1 spectra from MZA-format files, and you need to decide which peaks to retain based on their intensity.
    0 installs
48. ▌
    Peak Shape Correlation Analysis · holobiomicslab

    Use when when extracting benchmark peaks from mzML files for multiple isotopologues of target molecules, after initial m/z and retention-time matching, to validate that detected isotopologue peaks exhibit consistent peak shape and expected abundance ratios before including them in a reliability.
    0 installs
49. ▌
    Peptide Charge State Prediction · holobiomicslab

    Use when you have raw mass spectrometry data in MS1 format and need to assign charge states to peptide ions without manual curation or rule-based heuristics.
    0 installs
50. ▌
    Performance Benchmark Execution · holobiomicslab

    Use when you have access to a tool with published performance claims (e.g., '~20 seconds on M2 Macbook') and want to validate those claims on your own hardware, or you need to benchmark processing speed before committing to a tool for production use on similarly sized datasets.
    0 installs
51. ▌
    Pfam Domain Pattern Recognition · holobiomicslab

    Use when when you have a set of Biosynthetic Gene Clusters (BGCs) in GenBank format and need to identify statistically significant or topic-modeled co-occurrence patterns of Pfam domains and subPfams across multiple genes.
    0 installs
52. ▌
    Plage Method Metabolite Scoring · holobiomicslab

    Use when use PLAGE when you have log2-transformed, standardized metabolite intensity data (rows = peak features, columns = samples) with compound annotations (peak ID → metabolite database ID mappings), and you want to rank metabolite groupings (pathways, GNPS Molecular Families, MS2LDA.
    0 installs
53. ▌
    Pretrained Model Weight Loading · holobiomicslab

    Use when you have a pretrained PyTorch model checkpoint (e.g., JESTR weights for NPLIB1) and wish to apply it to rank candidate molecules or score spectra without modifying model parameters.
    0 installs
54. ▌
    Python Filter Class Inheritance · holobiomicslab

    Use when you need to filter compounds during Pickaxe network expansion based on domain-specific criteria (e.g., mass matching, similarity thresholds, retention time windows) that are not covered by built-in filters.
    0 installs
55. ▌
    Python Scientific Visualization · holobiomicslab

    Use when you have per-sample model predictions and metabolite signal intensities from a trained deep learning model (e.g., DeepMSProfiler) and need to visualize which metabolites correlate most strongly with specific disease phenotypes.
    0 installs
56. ▌
    Pytorch Forward Pass Validation · holobiomicslab

    Use when after instantiating a PyTorch model (such as TransG-Net) with multimodal inputs (graph features and SMILES embeddings), and before beginning model training.
    0 installs
57. ▌
    Pytorch Neural Network Training · holobiomicslab

    Use when you have a PyTorch model architecture (pretrained or freshly initialized), a dataset with molecular structures (as InChI strings or graph representations) and continuous target values (retention times in minutes), and you need to optimize model weights via supervised learning.
    0 installs
58. ▌
    Query Representation Validation · holobiomicslab

    Use when after parsing a MassQL query string into an abstract syntax tree or intermediate representation, before executing it against mass spectrometry data files (mzML, mzXML, etc.). Validation is essential when the query contains complex MS-specific patterns (e.
    0 installs
59. ▌
    R Syntax Validation And Linting · holobiomicslab

    Use when after editing R configuration scripts (e.g., Modular.r) that control execution modes (Modular vs Flow) or toggling analysis parameters (Lipid, TWeen_pos, PFAS). Apply this skill before integrating edited scripts into the LipidMatch-4.
    0 installs
60. ▌
    Raw Vendor File Format Handling · holobiomicslab

    Use when you have collected imaging mass spectrometry data in vendor-specific raw format (.raw files from Bruker, Waters, Thermo, or other instrument manufacturers) and need to convert it to the open, vendor-agnostic mzML XML format before downstream imzML construction and spatial alignment.
    0 installs
61. ▌
    Reaction Rule Coverage Analysis · holobiomicslab

    Use when when you need to decide how many reaction rules to include in a Pickaxe expansion run and want to quantify the coverage penalty of using a smaller subset; when benchmarking rule importance or frequency rankings;
    0 installs
62. ▌
    Reactive Pattern Implementation · holobiomicslab

    Use when when developing or extending a WPF-based GUI application (such as MsdialGuiApp) that requires declarative, composable handling of user interactions, real-time data binding, and asynchronous event streams.
    0 installs
63. ▌
    Record Filtering By Field Value · holobiomicslab

    Use when when you have a table of JSON records and need to select a subset matching a specific condition—for example, filtering records where 'status=active' before building a string value, or filtering 'experiment_type=MS' before constructing a matrix of dictionary objects.
    0 installs
64. ▌
    Reference Compound Verification · holobiomicslab

    Use when after formatting raw mass spectrometry transition data into the EISA-EXPOSOME schema (NAME, PrecursorMZ, ProductMZ, Intensity, RT, ID columns), and before exporting the final database file.
    0 installs
65. ▌
    Regex Capture Group Application · holobiomicslab

    Use when when you have PSM files (output from search engines like MaxQuant, MSGFPlus, or Sage) and spectrum files in mzML or MGF format with non-trivial or inconsistent naming schemes, and you need to establish which PSMs correspond to which spectra.
    0 installs
66. ▌
    Reproducibility Seed Management · holobiomicslab

    Use when before invoking random forest imputation (impute_rf) or any other stochastic algorithm on a MetaboSet expression matrix. Seed-setting is mandatory when reproducibility is required—either for method validation, peer review, or when sharing analysis code with collaborators.
    0 installs
67. ▌
    Search Performance Benchmarking · holobiomicslab

    Use when when you have two or more implementations of a spectral search tool (e.g., MASST vs. MASST+) and need to quantify whether claimed performance improvements (e.g., '100-fold speedup') are reproducible.
    0 installs
68. ▌
    Shiny Plot Export Configuration · holobiomicslab

    Use when when building or maintaining a Shiny GUI for omics data analysis that must support interactive visualization download in multiple raster and vector formats, and when the current plot export backend (orca) is deprecated, unmaintained, or incompatible with your deployment environment (e.
    0 installs
69. ▌
    Spectral Dimension Verification · holobiomicslab

    Use when after reading an imzML file (continuous or processed format) using readMSIData() in Cardinal, verify the resulting MSImagingExperiment object before performing normalization, baseline reduction, peak-picking, or statistical analysis.
    0 installs
70. ▌
    Spectral Peak Intensity Scaling · holobiomicslab

    Use when after filtering and noise removal when you have a cleaned spectrum with m/z and intensity pairs and need to normalize the intensity distribution prior to peptide fragment annotation, spectral library matching, or machine learning-based spectrum analysis.
    0 installs
71. ▌
    Spectrum Metadata Title Parsing · holobiomicslab

    Use when when you have PSM files from a search engine (e.g., MaxQuant, MSGFPlus, Mascot) and corresponding spectrum files in mzML or MGF format, and the spectrum identifiers in both files use different naming conventions or formats.
    0 installs
72. ▌
    Taxon Identifier Resolution API · holobiomicslab

    Use when you have a metadata table with raw, non-standardized taxonomy strings (e.g. misspellings, deprecated nomenclature, or aliases) in separate species, genus, and family columns, and you need to standardize them before performing taxon-dependent scoring (e.
    0 installs
73. ▌
    Technical Heterogeneity Removal · holobiomicslab

    Use when your metabolomics matrix (log2-scaled, samples × features in .csv format) exhibits spatial or distributional separation by batch/analytical run, visible in PCA or RLA plots.
    0 installs
74. ▌
    Thermodynamic Index Calculation · holobiomicslab

    Use when after molecular formula assignment and filtering of FT-ICR MS peaks, when you have elemental composition (C, H, O, N, S, P counts) and need to characterize metabolite thermodynamic stability, degree of oxidation, aromaticity, and unsaturation to compare compound reactivity across samples.
    0 installs
75. ▌
    Threshold Based Match Filtering · holobiomicslab

    Use when after calculating similarity metrics (e.g. cosine similarity or spectral correlation) between query peak networks and a simulated INADEQUATE database, when you need to distinguish true metabolite matches from spurious or low-confidence assignments and generate a curated list of identified.
    0 installs
76. ▌
    Unified Vocabulary Construction · holobiomicslab

    Use when when you have parallel mass spectra and molecular structure data (e.g., CANOPUS or MassSpecGym datasets) and aim to train a single encoder-decoder model (e.g., BART) that must handle both modalities as input and output tokens.
    0 installs
77. ▌
    Visualization Format Conversion · holobiomicslab

    Use when you have generated exploratory data analysis plots (PCA, correlation heatmaps, missing-variable plots) in the pmartR Shiny interface and need to download them as static images for inclusion in reports, manuscripts, or presentations with specific width, height, and resolution requirements.
    0 installs
78. ▌
    Web Service Health Verification · holobiomicslab

    Use when after deploying a containerized web application (e.g., via `docker run`), before proceeding to functional testing or integration. Use this skill to confirm the application server (Tomcat, etc.) has fully initialized and the web service is listening on the mapped port and URL path.
    0 installs
79. ▌
    Suspect Screening Exposomics Workflow · holobiomicslab bundle

    Use when you have untargeted HRMS data and want to screen for a defined suspect list of environmental / exposure-relevant compounds — detect features, match them to suspect-list entries by exact mass/RT/MS2, elucidate structures of hits by in-silico fragmentation, and assign identification confidence levels (Schymanski), producing a confidence-annotated suspect-hit table.
    0 installs
80. ▌
    Targeted Lcms Quantification Workflow · holobiomicslab bundle

    Use when you have targeted LC-MS data for a defined panel of analytes and want absolute or relative concentrations — extract and integrate the target transitions/ion chromatograms, build calibration curves from standards with internal-standard normalization, apply them to samples, and QC the batch (response drift, QC-sample RSD) to a reportable quantification table.
    0 installs
81. ▌
    Untargeted Lcmsms Annotation Workflow · holobiomicslab bundle

    Use when you have untargeted LC-MS/MS data (mzML) and want an annotated feature table — preprocessing, blank/QC filtering, feature-based molecular networking, spectral library matching, SIRIUS de novo annotation, optional taxonomy-aware re-weighting, and a fused master table. This is the canonical metabopipe-style annotation pipeline.
    0 installs
82. ▌
    Edger Dgeobject Construction · holobiomicslab

    Use when you have transcript-level abundance estimates and count matrices from tximport (derived from Salmon, Sailfish, or kallisto output) and need to prepare them for differential expression analysis in edgeR.
    0 installs
83. ▌
    Gene Set Enrichment Analysis · holobiomicslab

    Use when when you have a ranked list of gene-level statistics (e.
    0 installs
84. ▌
    Isoform Structure Annotation · holobiomicslab

    Use when when you have a GTF genome annotation and need to catalog all transcript isoforms and local alternative splicing event variants (exon skipping, intron retention, alternative splice sites, mutually exclusive exons, alternative first/last exons) before quantifying their inclusion levels.
    0 installs
85. ▌
    Rnaseq Count Matrix Analysis · holobiomicslab

    Use when you have a count matrix (genes × samples) from HTSeq, featureCounts, or transcript abundance quantification (Salmon, kallisto), a sample metadata table with experimental design, and you need to test for differential expression while controlling false discovery rate via independent.
    0 installs
86. ▌
    Umap Embedding Visualization · holobiomicslab

    Use when after completing PCA and k-nearest neighbor graph construction on preprocessed, log-normalized, highly-variable-gene-filtered single-cell RNA-seq data (stored in an AnnData object), compute UMAP embeddings when you need a 2-D visualization for cluster inspection, cell-type annotation, or.
    0 installs
87. ▌
    Ion Trace Extraction And Filtering · holobiomicslab

    Use when you have CE-MS raw data (mzML or netCDF format) containing a known target analyte with a precise m/z value, and you need to isolate its signal within a defined effective mobility window (e.
    0 installs
88. ▌
    Mass To Charge Tolerance Filtering · holobiomicslab

    Use when extracting migration times of specific analyte or reference markers (e.g., Paracetamol EOF marker) from CE-MS files using peak-picking workflows.
    0 installs
89. ▌
    Peak Picking Avoidance Ms Analysis · holobiomicslab

    Use when analyzing raw 2D MS data (m/z vs. retention time maps) where conventional peak picking introduces unacceptable error rates, particularly in untargeted metabolomics or chemometrics studies requiring sensitive marker identification at trace levels (e.g., parts per billion).
    0 installs
90. ▌
    Retention Time Prediction Modeling · holobiomicslab

    Use when you have a set of small-molecule compounds (e.g., from MS/MS library matching or database annotation) that require retention time validation or ranking to resolve ambiguous identifications.
    0 installs
91. ▌
    Retrieval Metric Hit K Calculation · holobiomicslab

    Use when when you have generated embeddings for query and reference MS/MS spectra, computed a cosine similarity matrix between them, and need to evaluate how often the correct compound appears in the top-1, top-5, or top-10 retrieved candidates.
    0 installs
92. ▌
    Chromatographic Peak Detection Msw · holobiomicslab

    Use when you have raw mzML files from an FTICR-MS or other direct-injection MS instrument and need to identify discrete chromatographic peaks across the m/z and retention-time dimensions. Use this skill when you must isolate individual ion signals before applying calibration corrections (e.
    0 installs
93. ▌
    Condition Effect Matrix Generation · holobiomicslab

    Use when you need to create a synthetic feature table with known, ground-truth condition effects for method validation when: (1) testing normalization or batch-correction algorithms that must not confound condition signal with batch noise;
    0 installs
94. ▌
    Ground Truth Intensity Calculation · holobiomicslab

    Use when when generating synthetic LC/GC-MS .mzML files with companion ground-truth peak tables for method validation, you need to calculate the absolute maximum intensity that each simulated peak would exhibit in the raw mass spectrometry matrix.
    0 installs
95. ▌
    Linear Algebra Peak Reconstruction · holobiomicslab

    Use when after a Transformer model (e.g. GCMSFormer) has predicted the pure mass spectral matrix S for all components in overlapped peaks.
    0 installs
96. ▌
    Mass Spectral Component Extraction · holobiomicslab

    Use when raw GC-MS data (netCDF or mzML format) contains overlapping chromatographic peaks with co-eluting ions that cannot be resolved by retention time alone.
    0 installs
97. ▌
    Mass Spectrometry Feature Grouping · holobiomicslab

    Use when after raw data processing and feature extraction (e.g., via XCMS, OpenMS, or enviPick) when you have detected features across multiple LC-MS or GC-MS analyses and need to identify which features represent the same chemical across samples.
    0 installs
98. ▌
    Mass Spectrometry Library Matching · holobiomicslab

    Use when when you have an unknown MS/MS spectrum (with ≥10 peaks, precursor m/z, and at least 5 fragment ions) and need to identify it by comparing against a curated spectral library with annotated InChIKeys or chemical structures.
    0 installs
99. ▌
    Metabolomics Software Benchmarking · holobiomicslab

    Use when you have completed peak picking with two or more competing tools (e.g., IDSL.IPA, MZmine 2, xcms, MS-DIAL) on the same LC/HRMS dataset(s) and need to quantify which performs better. Use this skill when tool selection claims require validation (e.g., 'IDSL.
    0 installs
100. ▌
     Modulation Parameter Configuration · holobiomicslab

     Use when you have a raw GCxGC-MS chromatogram in NetCDF format (.cdf file) and need to import it into R as a 2D-TIC object for preprocessing (smoothing, baseline correction, peak alignment) or multivariate analysis.
     0 installs