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HolobiomicsLab

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1. ▌
   Gnn Architecture Design For Molecular Graphs · holobiomicslab

   Use when when you have preprocessed molecular graph data (node and edge tensors representing atoms and bonds) and need to train a regression model to predict a continuous molecular property (e.g., LC retention time).
   0 installs
2. ▌
   Graph Based Metabolite Similarity Assessment · holobiomicslab

   Use when you have a collection of MS/MS spectra (stored as Spectrum2 objects in an ms2Lib class) and need to identify which spectra share identical fragmentation patterns—particularly when coupled to a GNPS molecular network to focus on explaining network components (connected components, cliques.
   0 installs
3. ▌
   Ion Mobility Saturation Detection And Repair · holobiomicslab

   Use when preprocessing raw Agilent MassHunter (.d) or UIMF IM-MS data files that exhibit signal saturation—ion intensity clipping caused by detector or amplifier limits—which distorts peak shape and abundance estimates across the m/z and drift-time axes.
   0 installs
4. ▌
   Lcims Msms Data Preprocessing Peak Detection · holobiomicslab

   Use when you have loaded mzML.gz or HDF5-formatted raw LC-IMS-MS/MS data and need to identify discrete peaks before feature alignment. Use it if your goal is to reduce noise, increase signal-to-noise ratio, and prepare multi-dimensional data for cross-sample feature matching and CCS calibration.
   0 installs
5. ▌
   Linear Regression Fitting For Chromatography · holobiomicslab

   Use when you have extracted retention times at peak maxima (rtFittedAPEX) from extracted-ion chromatograms (XICs) of known internal RT calibrants (e.
   0 installs
6. ▌
   Log Transform Normalization For Metabolomics · holobiomicslab

   Use when after chromatographic peak detection, fill-in of missing peaks, and retention-time-based grouping in LC-MS metabolomics workflows, apply log2 transformation when refining feature groups using correlation of abundances across samples.
   0 installs
7. ▌
   Mass Spectrometry Data Constraint Validation · holobiomicslab

   Use when implementing replacement methods ($<-, [<-, spectraData<-, mz<-, intensity<-, peaksData<-) for a writable MsBackend subclass, or when modifying peak data in an existing backend.
   0 installs
8. ▌
   Mass Spectrometry Feature Extraction Ms1 Ms2 · holobiomicslab

   Use when when you have raw mzML files from LC-MS/MS metabolomics experiments and need to convert them into a structured feature table with accurate mass, retention time, and MS2 spectral data linked to a reference compound list.
   0 installs
9. ▌
   Mass Spectrometry Feature Table Construction · holobiomicslab

   Use when you have vendor-independent centroided mzML files from LC- or GC-HRMS data acquired in data-dependent acquisition (ddMS2) mode and need to extract detected features with m/z, retention time, and intensity attributes as input for non-target screening or PFAS prioritization workflows.
   0 installs
10. ▌
    Mass Spectrometry Quality Metrics Extraction · holobiomicslab

    Use when you have centroided .mzML LC–MS data, a validated target compound list with adjusted expected retention times (e.g., after a screening mode run), and need to quantify peak quality and integration reliability across multiple sample runs to support metabolomics or lipidomics workflows.
    0 installs
11. ▌
    Mass Spectrometry Reference Standard Mapping · holobiomicslab

    Use when you have acquired tunemix data (positive or negative ion mode, in .h5 format) with known CCS reference values and need to construct a calibration function that will later predict CCS values for unknown analytes.
    0 installs
12. ▌
    Mass Spectrometry Spectrum Quality Filtering · holobiomicslab

    Use when compiling or harmonizing MS/MS spectral libraries from multiple source repositories and you need to identify and remove spectra that fail quality thresholds (low resolution, precursor-fragment mass inconsistency, duplicate fragment patterns, noise-dominated, or missing critical metadata.
    0 installs
13. ▌
    Mass Spectrometry Transition Data Formatting · holobiomicslab

    Use when when you have raw mass spectrometry transition data from a triple-quadrupole or other tandem MS instrument and need to prepare it for suspect chemical screening using EISA-EXPOSOME, or when merging custom compound libraries into the T3DB format.
    0 installs
14. ▌
    Mass2motif Probability Distribution Learning · holobiomicslab

    Use when when you have preprocessed MS/MS spectra converted to a bag-of-fragments format (fragments and neutral losses extracted, noise filtered) and you seek to discover recurring fragmentation patterns without prior compound identification.
    0 installs
15. ▌
    Metabolite Feature Association Across Labels · holobiomicslab

    Use when after PuInc_seeker has identified putative incorporations (m/z features showing significant fold-change and p-value signals between labeled and unlabeled sample groups) and you need to assign base peaks—the most intense isotopologue signals—and validate isotope-pair mass gaps match.
    0 installs
16. ▌
    Metabolite Feature Correspondence Validation · holobiomicslab

    Use when after m/z grouping and pairwise alignment detection when you have a metabCombiner object containing candidate feature pair alignments and need to select a subset of mutually abundant, high-confidence anchors to anchor a nonlinear retention time mapping spline.
    0 installs
17. ▌
    Metabolite Structural Annotation Integration · holobiomicslab

    Use when after statistical analysis (e.g., MB-PLS with permutation testing) has identified a subset of significant LC-MS features (p < 0.05 or similar threshold) that require structural interpretation.
    0 installs
18. ▌
    Metabolomic Molecular Family Networking Gnps · holobiomicslab

    Use when when you have untargeted LC-MS/MS spectral data from microbial or environmental samples and aim to group related metabolites into molecular families for natural product discovery, especially when integrating with genomic biosynthetic gene cluster (BGC) annotations to link chemistry to.
    0 installs
19. ▌
    Metabolomics Feature Intensity Normalization · holobiomicslab

    Use when after peak detection and feature table construction (rows = features, columns = samples with intensity values) and before applying intensity-based filters (e.g., fold-change, phenotype score) or when preparing data for dashboard visualization.
    0 installs
20. ▌
    Metabolomics Quantification Table Processing · holobiomicslab

    Use when you have a quantification table (rows = metabolite features, columns = samples with abundance values), corresponding metadata table (sample annotations, groupings), and spectral data files, and you need to produce a unified JSON dashboard artifact that can be loaded into an interactive.
    0 installs
21. ▌
    Microbe Metabolite Prediction Neural Network · holobiomicslab

    Use when you have paired microbiome (16S or metagenomic taxonomy/functions at genus or finer level) and metabolome (LC-MS or similar profiled metabolites) data from the same samples and want to: (1) predict unobserved metabolite abundances from microbiome composition;
    0 installs
22. ▌
    Missing Value Imputation For Column Metadata · holobiomicslab

    Use when when preparing raw HPLC column parameter arrays for featurization into feature vectors for retention time prediction models. Specifically apply this skill when column metadata contains empty strings (indicating missing diameter or pH values) or non-standard string encodings (e.g., '2.
    0 installs
23. ▌
    Missing Value Replacement By Feature Minimum · holobiomicslab

    Use when after loading a feature table into memory when the table contains zero or missing values that represent true signal loss (not genuine absence), and you need to impute them before normalization, batch correction, or statistical analysis.
    0 installs
24. ▌
    Molecular Formula Computation From Structure · holobiomicslab

    Use when processing tandem MS/MS libraries in mgf format (such as GNPS) that lack a Molecular Formula (MF) field but contain valid SMILES strings. The computed formulas are required before combining libraries or writing them to msp format for MS-DIAL compatibility.
    0 installs
25. ▌
    Classification Performance Metric Evaluation · holobiomicslab

    Use when after training multiple classifiers (traditional ML and deep learning) on a preprocessed metabolomics feature matrix with labeled samples, and you need to quantify and compare their predictive performance to select the model or ensemble for downstream analysis.
    0 installs
26. ▌
    Cross Member Metabolic Dependency Resolution · holobiomicslab

    Use when when you have consensus metabolic reconstructions for multiple community members (e.
    0 installs
27. ▌
    Cross Platform Reproducibility Configuration · holobiomicslab

    Use when when you have documented pinned package versions for a Python-based scientific implementation (e.g., from a README or project documentation) and need to distribute a reproducible computational environment to other users or CI/CD systems.
    0 installs
28. ▌
    Cyp450 Metabolite Prediction API Integration · holobiomicslab

    Use when you need to embed CYP450 metabolite prediction directly into a larger Java software pipeline or require dynamic toggling of the CypReact filter module based on experimental parameters.
    0 installs
29. ▌
    Data Format Conversion To Application Schema · holobiomicslab

    Use when you have m/z peak lists (positive and negative mode) and sample metadata from peak-picking software (e.g., XCMS with MetaboAnalyst export, MSnbase, or MetaboLights format) and need to load them into MetaboShiny for compound identification, statistical analysis, or machine learning.
    0 installs
30. ▌
    Dependency Resolution For Build Environments · holobiomicslab

    Use when when preparing to build LipidSpace or similar desktop/CLI applications from source across multiple target platforms (Windows 10, Ubuntu 22.04, macOS 12+ ARM64), or when encountering build failures due to missing headers, libraries, or incompatible tool versions.
    0 installs
31. ▌
    Deployment Mode Detection And Fallback Logic · holobiomicslab

    Use when building a Streamlit application that must support both cloud deployments (with Redis task queuing) and local/offline execution (with multiprocessing), and you need to automatically select the execution path without requiring separate code paths or manual configuration switches at runtime.
    0 installs
32. ▌
    Diagnostic Plot Generation For Batch Effects · holobiomicslab

    Use when after loading log-transformed metabolomics feature abundance tables (samples as rows, metabolic features as columns) with batch identifiers, and before committing to a single batch-correction model.
    0 installs
33. ▌
    Directional Effect Assignment Across Studies · holobiomicslab

    Use when you have harmonized metabolite results from multiple independent studies, each with fold-change or trend classification data but no variance/standard deviation, and you need to produce a qualitative consensus on directionality for each compound.
    0 installs
34. ▌
    Duplicate Record Detection And Deduplication · holobiomicslab

    Use when when merging metabolomic data from multiple studies, you have compound identifiers in heterogeneous formats (chemical names, InChI, InChIKey, SMILES) and need to detect whether the same compound appears under different representations.
    0 installs
35. ▌
    Feature Matrix Preparation Mass Spectrometry · holobiomicslab

    Use when when you have raw mass spectrometry spectral data (peak intensities across m/z values) and need to feed it into MLP or GNN models for metabolite annotation, or when you need to generate LDA topic labels as auxiliary multi-task learning targets.
    0 installs
36. ▌
    Feature Metadata Alignment Across Dimensions · holobiomicslab

    Use when you have loaded a feature-by-pixel intensity matrix from an MSI HDF5 container and need to perform dimension-preserving corrections (e.
    0 installs
37. ▌
    Ft Icr Ms Data Processing Pipeline Execution · holobiomicslab

    Use when you have FT-ICR MS peak abundance data in Formularity .
    0 installs
38. ▌
    Gap Filling And Reaction Conflict Resolution · holobiomicslab

    Use when when merging multiple draft metabolic models (in JSON, XML, or SBML format) from community members or assembly variants and you encounter conflicting reaction annotations, missing metabolic pathways, or incomplete gap-filling decisions that require arbitration across inputs.
    0 installs
39. ▌
    Gene Protein Reaction Association Evaluation · holobiomicslab

    Use when you have a constraint-based metabolic model with embedded GPR rules (AND/OR associations between genes and reactions), paired with quantified gene-expression data (RNA-seq FPKM or read counts per cell line).
    0 installs
40. ▌
    Imaging Mass Spectrometry Ion Identification · holobiomicslab

    Use when you have imaging mass spectrometry data from spatial metabolomics experiments and need to reduce the high-dimensional peak space to a ranked set of marker ions for downstream spatial analysis (e.g., tissue region annotation or biomarker discovery).
    0 installs
41. ▌
    In Source Fragment Adduct Candidate Flagging · holobiomicslab

    Use when you have aligned, imputed time-resolved mass spectrometric data from direct-injection plasma ionization (e.g., DBDI, DESI) without chromatographic separation, and you suspect multiple m/z features belong to the same neutral analyte as in-source fragments or oxygen-bound adducts.
    0 installs
42. ▌
    Isobaric Ion Misclassification Documentation · holobiomicslab

    Use when after matrix annotation has been performed on mass spectrometry imaging (MSI) data when you need to identify and document ions whose m/z values overlap with or are isobaric to other peaks, creating risk of false positive or false negative matrix assignments.
    0 installs
43. ▌
    Linear Regression Design Matrix Construction · holobiomicslab

    Use when after log-transformation and missing-value imputation of featuredata (via LogTransform and MissingValues functions), when you have normalized metabolomics intensity data and need to identify metabolites associated with specific biological or experimental factors encoded as covariates in a.
    0 installs
44. ▌
    Mass Spectra Tokenization Unified Vocabulary · holobiomicslab

    Use when when you have paired mass spectra and molecular structure data and need to train a unified model for structure elucidation. Use this skill at the data preparation stage before pretraining, when you want both modalities to share representational capacity rather than operate in isolation.
    0 installs
45. ▌
    Mass Spectrometry Intensity Drift Correction · holobiomicslab

    Use when mS quantification data exhibits intensity drift—a systematic decline or variation in detector response across the run sequence. Intensity drift is particularly common in long measurement sessions and compromises the accuracy of feature-by-sample intensity matrices.
    0 installs
46. ▌
    Metabolite Database Identifier Normalization · holobiomicslab

    Use when you have metabolomics metadata in mwTab or tabular format with column headers and values that may contain database identifiers (e.g., HMDB IDs, PubChem CIDs, KEGG compound IDs) in heterogeneous or non-canonical formats (mixed case, optional prefixes, variable naming conventions).
    0 installs
47. ▌
    Metabolomic Network Edge Type Prioritization · holobiomicslab

    Use when when your metabolomic network contains multiple edge types (Biochemical, Structural, Mass Spectral, Correlation) between the same node pairs and you want to export a unique-edge network in which each node pair is connected by exactly one edge—the one with highest priority according to the.
    0 installs
48. ▌
    Metabolomics Feature Detection And Alignment · holobiomicslab

    Use when you have raw metabolomics mass spectrometry data in mzML or mzXML format and need to extract, align, and normalize metabolic features across multiple samples or conditions.
    0 installs
49. ▌
    Missing Data Handling In Metabolite Datasets · holobiomicslab

    Use when when importing metabolomics datasets with multiple studies into amanida_read for quantitative or qualitative meta-analysis, and some studies report missing values for p-values, fold-changes, sample sizes, or other effect size metrics.
    0 installs
50. ▌
    Multi Factorial Experimental Design Handling · holobiomicslab

    Use when your lipidomics dataset includes multiple experimental factors (e.
    0 installs
51. ▌
    Multicontrast Statistical Testing Lipidomics · holobiomicslab

    Use when after removing outlier samples and confirming data quality through PCA or TIC plots, apply this skill when you need to quantify statistical significance of lipid abundance differences across defined sample groups (e.g., disease vs. control, treatment vs. untreated, cancer stages).
    0 installs
52. ▌
    Multivariate Metabolomic Statistical Testing · holobiomicslab

    Use when after WGCNA-derived metabolic modules have been identified and named in a normalized, imputed MultiAssayExperiment object, and you need to test whether specific modules show statistically significant association with a binary or categorical sample grouping (e.
    0 installs
53. ▌
    Neural Network Early Stopping Implementation · holobiomicslab

    Use when when training a multilayer perceptron neural network on paired microbiome-metabolome datasets where you have a held-out validation fold (20% of each cross-validation fold) and wish to prevent overfitting without manual epoch selection.
    0 installs
54. ▌
    Peak Table Imputation Missing Value Handling · holobiomicslab

    Use when after peak clustering in a GCIMS preprocessing pipeline, when the peak table matrix contains NA values corresponding to peaks detected in some samples but not others, and you have computed cluster statistics that characterize each peak cluster's properties.
    0 installs
55. ▌
    Ppm Tolerance Filtering In Mass Spectrometry · holobiomicslab

    Use when when you have assigned molecular formulas to m/z peaks or computed mass differences between peaks in FT-ICR MS data, and you need to distinguish true chemical matches from noise or random coincidences.
    0 installs
56. ▌
    Python Package Installation Development Mode · holobiomicslab

    Use when when you have cloned a Python package repository locally and need to test code changes, run the package's test suite, or contribute to development without reinstalling the package after each modification.
    0 installs
57. ▌
    Quality Control Sample Selection And Marking · holobiomicslab

    Use when your metabolomics dataset contains samples analyzed across multiple batches or runs, and you have sample-level metadata (sampledata) with a 'type' or classification field. You intend to apply QC-aware normalization methods (e.
    0 installs
58. ▌
    Quantitative Mode Metabolomics Configuration · holobiomicslab

    Use when when you have metabolomics results from multiple studies reporting compound identifiers, p-values, fold-changes, and study sizes (N), and you need to prepare them for quantitative meta-analysis using weighted Fisher's method and logarithmic fold-change combination.
    0 installs
59. ▌
    Rdkit Descriptor And Fingerprint Calculation · holobiomicslab

    Use when you need to (1) compare structural similarity between generated compounds and target/reference structures using Tanimoto similarity scores, (2) extract molecular descriptors for machine learning models that predict reaction feasibility, (3) implement compound filtering based on chemical.
    0 installs
60. ▌
    Reaction Activity Score Computation From Gpr · holobiomicslab

    Use when you have RNA-seq FPKM abundance data for genes across multiple cell lines or samples, a metabolic model with embedded GPR associations, and need to translate differential gene expression into reaction-level constraints for flux prediction.
    0 installs
61. ▌
    Repository Cloning With Recursive Submodules · holobiomicslab

    Use when you need to set up a development environment for a project that declares Git submodules (typically listed in .gitmodules), particularly when the build system (qmake, make, Maven, etc.) expects all dependencies to be present in the working tree.
    0 installs
62. ▌
    Rna Seq Preprocessing Pipeline Orchestration · holobiomicslab

    Use when when you have raw FASTQ files (from SRA or local storage) and need to produce normalized transcript quantification (quant.sf) files for a multi-sample RNA-seq cohort.
    0 installs
63. ▌
    Roc Auc Computation For Phenotype Prediction · holobiomicslab

    Use when you have constructed consensus-clustered microbe and metabolite modules from microbiome-metabolome interaction data and wish to test whether these module-level features have clinically predictive value for a binary phenotype (e.g., disease vs. healthy).
    0 installs
64. ▌
    Spectra Object Serialization Deserialization · holobiomicslab

    Use when you have Spectra objects in an R environment and need to apply Python MS algorithms (e.g., matchms similarity scoring, spectrum normalization, or filtering) that operate on Python spectral objects, then return results back to R for further analysis or visualization.
    0 installs
65. ▌
    Spectral Array Extraction And Reconstruction · holobiomicslab

    Use when your input is an mzPeak archive (ZIP of Parquet files) and you need to recover spectrum signal data (m/z values and intensities) for downstream analysis, visualization, or format conversion. Use this skill when working with profile or centroid mode spectra stored in `spectra_data.
    0 installs
66. ▌
    Spectral Similarity Scoring With Mass Shifts · holobiomicslab

    Use when you have an unknown query spectrum suspected to carry a post-translational modification and need to match it against a library of unmodified reference spectra.
    0 installs
67. ▌
    Standardized Region Export For Deep Learning · holobiomicslab

    Use when you have LC-HRMS profile-mode data with detected local maxima (from gradient-descent peak finding) and need to prepare them as input for a convolutional neural network trained to classify peaks vs. background signal or to estimate peak boundaries and centers.
    0 installs
68. ▌
    Tensor Shape Validation Through Forward Pass · holobiomicslab

    Use when after assembling a Graphormer backbone with DGL molecular graph encoders, column-parameter embedding layers, and gradient-slope feature concatenation, but before training on the full dataset.
    0 installs
69. ▌
    Topic Label Validation Distribution Analysis · holobiomicslab

    Use when after LDA topic inference has assigned dominant topic labels to mass spectra, and before those labels are passed to MLP or GNN multi-task training.
    0 installs
70. ▌
    Univariate Statistical Output Interpretation · holobiomicslab

    Use when after running omu_summary (t-test) or omu_anova (ANOVA) on metabolomics count data with a defined contrast (e.g., numerator vs. denominator treatment levels), when you need to filter and visualize metabolites by statistical significance and effect size.
    0 installs
71. ▌
    W4m Three Table Format Conformance · holobiomicslab

    Use when moving a feature table between Workflow4Metabolomics tools and the dataMatrix, sampleMetadata and variableMetadata files must agree on identifiers, order and R-name validity before a statistics step silently analyses mislabelled samples.
    0 installs
72. ▌
    Dask Array Materialization And Collection · holobiomicslab

    Use when you have performed lazy dask-backed feature extraction on an ImageContainer using im.calculate_image_features and need to persist the computed spatial features into the AnnData object while controlling when and how dask graph computation is triggered.
    0 installs
73. ▌
    Differential Splicing Statistical Testing · holobiomicslab

    Use when you have PSI (percent-spliced-in) matrices for multiple samples grouped into two or more biological conditions, along with corresponding transcript expression quantification, and need to identify events or transcripts with statistically significant changes in inclusion levels between.
    0 installs
74. ▌
    Gene Level Summarization From Transcripts · holobiomicslab

    Use when you have transcript-level quantification files (salmon quant.sf.gz, kallisto h5, or Sailfish output) and need to perform gene-level differential expression analysis.
    0 installs
75. ▌
    Multiple Testing Correction Visualization · holobiomicslab

    Use when after running fgsea() on a preranked gene list and obtaining a results table with raw pval, padj, ES, NES, and size columns, use this skill to: (1) subset results to top enriched pathways (e.g., top 10 upregulated ES > 0 and top 10 downregulated ES < 0 by adjusted p-value);
    0 installs
76. ▌
    Rna Seq Experimental Design Specification · holobiomicslab

    Use when before constructing a DESeqDataSet from count data or tximport output, when you have raw RNA-seq samples that need to be annotated with experimental conditions, treatment groups, batch effects, or other covariates.
    0 installs
77. ▌
    Salmon Quantification Output Verification · holobiomicslab

    Use when after running salmon quant with the --writeMappings/-z flag to produce SAM output, or when investigating discrepancies between the number of mapped reads reported in quant.sf and the actual number of records written to the output SAM file.
    0 installs
78. ▌
    Sparse Matrix Verification And Validation · holobiomicslab

    Use when after calling squidpy.gr.spatial_neighbors or any graph-building operation that outputs sparse matrices to adata.
    0 installs
79. ▌
    Transcript Abundance Correlation Analysis · holobiomicslab

    Use when when validating a new or reimplemented quantification tool against a reference implementation on the same dataset and index, or when investigating whether changes to seed representation, chain pruning thresholds, or other algorithmic parameters affect downstream abundance estimates.
    0 installs
80. ▌
    Uncertainty Aware Significance Assessment · holobiomicslab

    Use when you have PSI matrices for two or more conditions with replicates per condition, and you need to determine which alternative splicing events show significant changes between conditions while accounting for measurement uncertainty that scales with transcript expression levels.
    0 installs
81. ▌
    Approximate Nearest Neighbor Index Construction · holobiomicslab

    Use when when you have a large collection of reference MS/MS spectra (spectral library) and need to search unknown query spectra against it rapidly, particularly for open modification searching where the modification mass is unknown and candidate space is large.
    0 installs
82. ▌
    Ce Ms Migration Time To Mobility Transformation · holobiomicslab

    Use when your CE-MS dataset exhibits migration time drift between runs due to electroosmotic flow (EOF) variation, and you have identified two internal mobility markers (e.g., Paracetamol and Procaine) with known charges whose migration times can be measured in the raw data.
    0 installs
83. ▌
    Chromatographic Peak Detection And Segmentation · holobiomicslab

    Use when you have raw LC-MS data (mzML or vendor format) and need to discover and characterize all chromatographic features present, without prior knowledge of target analytes.
    0 installs
84. ▌
    Marker Feature Identification Chromatography Ms · holobiomicslab

    Use when when processing raw chromatography–mass spectrometry data (GC–MS or LC–MS) as a 2D m/z vs retention time map and you need to identify and visualize marker features for analyte discrimination without relying on conventional peak picking.
    0 installs
85. ▌
    Mass Spectral Missing Word Fraction Computation · holobiomicslab

    Use when when applying a pre-trained Spec2Vec Word2Vec model to new mass spectra (particularly those outside the model's training distribution), you need to assess whether peaks and neutral losses in query spectra have been seen during model training.
    0 installs
86. ▌
    Mass Spectral Similarity Scoring Across Samples · holobiomicslab

    Use when after XCMS feature detection, grouping, and retention time correction when you have aligned features with consistent retention times and intensity patterns across samples.
    0 installs
87. ▌
    Metabolite Feature Clustering By Retention Time · holobiomicslab

    Use when after XCMS feature detection, grouping, retention time correction, regrouping, and missing value filling on LC-MS or GC-MS data, when you have an aligned feature table with retention times and intensity profiles across multiple samples and need to collapse redundant features into.
    0 installs
88. ▌
    Performance Metric Extraction From Publications · holobiomicslab

    Use when you have identified a claim that one tool outperforms another (e.g., 'IDSL.IPA outperforms MZmine 2 and xcms') in a research article's abstract or introduction, but the specific metrics and results table are not included in the introductory text.
    0 installs
89. ▌
    Bag Of Words Document Representation Generation · holobiomicslab

    Use when you have raw MS/MS spectral data in standard mass spectrometry formats and need to prepare it for unsupervised substructure discovery via topic modeling.
    0 installs
90. ▌
    Biochemical Relation Integration For Annotation · holobiomicslab

    Use when when you have LC/MS feature data (m/z, retention time, intensity) that must be annotated against a metabolic database and you have access to (or can construct) knowledge about biochemical reaction networks, expected isotope patterns, and instrument-specific adduct formation rules.
    0 installs
91. ▌
    Bioconductor Summarized Experiment Construction · holobiomicslab

    Use when after successfully reading and validating a tab-delimited metabolomics file (containing mandatory columns: aliquot, compound, area, type, injection_time, batch) using readData, and before applying batch correction, outlier detection, or other QC filters.
    0 installs
92. ▌
    Blank Sample Background Interference Estimation · holobiomicslab

    Use when after MS1 feature detection and accurate mass annotation, when you have identified a set of blank injections (negative controls) run in the same analytical sequence segment as your biological or study samples.
    0 installs
93. ▌
    Checkpoint Selection Based On Validation Metric · holobiomicslab

    Use when training neural networks on MS/MS spectra (or similar scientific data) where you need to preserve model states that improve validation performance.
    0 installs
94. ▌
    Chemical Structure Transformation Documentation · holobiomicslab

    Use when when you have access to source code or algorithmic documentation of a metabolite generation pipeline (such as MAGMa's job subproject) and need to understand, validate, or reconstruct the transformations that convert a parent compound into enumerated metabolite candidates.
    0 installs
95. ▌
    Collision Cross Section Matching And Annotation · holobiomicslab

    Use when when you have LC-IM-MS/MS data with measured collision cross section (CCS) values and m/z assignments, and you need to disambiguate sterol isomers (particularly N-Me derived unsaturated sterols) by matching against a curated database of predicted CCS values and MS/MS fragmentation patterns.
    0 installs
96. ▌
    Collision Energy Optimization For Fragmentation · holobiomicslab

    Use when when you have N-Me derivatized unsaturated sterol lipid structures (as SMILES or molecular formula) and need to predict MS/MS fragmentation patterns with collision-energy-dependent m/z values and intensities for downstream CCS prediction or LC-IM-MS/MS library matching.
    0 installs
97. ▌
    Concentration Prediction From Calibration Model · holobiomicslab

    Use when you have (1) a set of calibration samples with known spiked concentrations of target compounds, (2) measured compound/internal-standard ratios for both calibration and study samples, and (3) need to convert ratios to absolute concentrations for reporting.
    0 installs
98. ▌
    Dynamic Exclusion Weighting Strategy Evaluation · holobiomicslab

    Use when you have prototyped a novel data-dependent acquisition strategy that uses dynamic exclusion with intensity or ROI weighting, and you need to quantitatively compare its MS/MS coverage and intensity performance against a simpler baseline (TopN) before testing on real instrumentation.
    0 installs
99. ▌
    Internal Standard Peak Detection And Validation · holobiomicslab

    Use when you have loaded processed LC-MS data (mzML or vendor format) and need to establish baseline instrument performance before evaluating sample analytes. Use it at the start of each LC-MS batch or run to ensure that internal standard detection passes predefined thresholds;
    0 installs
100. ▌
     Ionization Mode Specific Preprocessing Handling · holobiomicslab

     Use when you have raw MS/MS spectra in supported formats (.mgf, .mzML, or .msp) from mixed ionization modes and need to prepare them for downstream topic modeling (LDA) or motif discovery.
     0 installs