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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Gc Ms Molecular Family Organization 2 · holobiomicslab

   Use when after auto-deconvolution of GC-MS data has produced a table of individual deconvolved mass spectra (one per detected peak), and your goal is to group spectra into molecular families based on mass spectral similarity rather than retention time or chemical class.
   8 installs
2. ▌
   Graph Neural Network Encoder Design 2 · holobiomicslab

   Use when when you need to compare spectrum prediction models fairly across different encoder architectures (GNN vs. FFN vs. Transformer), and you require equivalent settings (same covariates, identical hyperparameter sweeps) to isolate the effect of the encoder design.
   8 installs
3. ▌
   Hrms Feature Annotation Integration 3 · holobiomicslab

   Use when you have LC- or GC-HRMS data in mzML format and a feature list (CSV/TSL/Excel) from external feature detection software (e.
   10 installs
4. ▌
   In Silico Spectrum Generation Cfmid 2 · holobiomicslab

   Use when when you have a list of SMILES strings representing chemical structures and need to create paired SMILES-spectrum training data for a generative model (like MSGO) without requiring experimental mass spectra.
   8 installs
5. ▌
   Installation Requirement Validation 2 · holobiomicslab

   Use when before attempting to run QCxMS2 for the first time, after updating any external dependencies (xtb, CREST, molbar, orca, geodesic_interpolate), or when troubleshooting unexplained calculation failures.
   11 installs
6. ▌
   Intensity Normalization And Scaling 3 · holobiomicslab

   Use when when working with raw or filtered MsmsSpectrum objects where peak intensities span a wide dynamic range and need to be normalized for downstream spectrum comparison, database matching, or publication-quality visualization.
   8 installs
7. ▌
   Intensity Threshold Noise Filtering 3 · holobiomicslab

   Use when you have loaded a raw or partially processed MsmsSpectrum object and need to reduce spectral noise before annotation, matching, or visualization. Use it especially when spectra contain many weak peaks (e.
   11 installs
8. ▌
   Isotopologue Pattern Detection Lcms 2 · holobiomicslab

   Use when after filtering LC-MS features by statistical significance (e.g., p-value < 0.01) and you wish to group features that represent the same metabolite at different isotopologue states.
   12 installs
9. ▌
   Java Application Build Verification 2 · holobiomicslab

   Use when when you need to confirm that a Java project's GitHub Actions workflow (e.g., 'dev_build_release.yml') has completed successfully and generated usable build artifacts;
   10 installs
10. ▌
    Lc Hrms Data Preprocessing Pipeline 3 · holobiomicslab

    Use when you have raw LC-HRMS metabolomics data in .mzML or .abf format and need to perform peak detection, feature alignment, and metabolite annotation in a reproducible, containerized environment.
    10 installs
11. ▌
    Singularity Container Backend Setup 3 · holobiomicslab

    Use when your LC-HRMS metabolomics analysis must run on a high-performance computing cluster (e.g., HiPerGator, SLURM-managed systems) that lacks Docker support or prefers Singularity for security and portability. You have .mzML or .
    13 installs
12. ▌
    Skyline Import Format Specification 2 · holobiomicslab

    Use when you have computationally generated precursor m/z values, fragment m/z values, collision energies, and retention time predictions for a set of lipid targets (e.
    11 installs
13. ▌
    Sparse Distance Matrix Construction 3 · holobiomicslab

    Use when you have a large collection of MS/MS spectra (hundreds of thousands to millions) that need to be clustered, you have already constructed nearest neighbor indexes on low-dimensional spectrum vectors (via feature hashing), and you need to compute only the relevant pairwise distances between.
    8 installs
14. ▌
    Spectral Match Result Consolidation 3 · holobiomicslab

    Use when you have executed batch searches of MS/MS spectra against multiple domain-specific MASST indices and need to integrate the resulting match outputs into a single coherent view.
    9 installs
15. ▌
    Spectral Quality Control Assessment 2 · holobiomicslab

    Use when after MS1 extraction (coarse/fine error correction, EIC window extraction) and retention time windowing on a set of mzML files tagged with ionization mode and compound adducts.
    10 installs
16. ▌
    Transformer Based Fragment Assembly 2 · holobiomicslab

    Use when when you have CNN-encoded spectral features (¹H and/or ¹³C NMR) and a set of predicted or candidate molecular fragments, and you need to determine which fragments are present and how they connect to form a valid molecular structure.
    9 installs
17. ▌
    Workflow Architecture Documentation 3 · holobiomicslab

    Use when you need to understand how a complex MS/MS spectral search system routes query spectra through multiple parallel processing pipelines with different objectives (e.g., reliable exact matching vs. fast approximate matching).
    7 installs
18. ▌
    Gradient Based Saliency Mapping 3 · holobiomicslab

    Use when you have a trained graph neural network model for CCS prediction and need to identify which molecular structural features drive individual predictions or systematic biases.
    11 installs
19. ▌
    Ion Mobility Reference Matching 3 · holobiomicslab

    Use when you have raw arrival-time data from TWIM-MS and need to convert it to collision cross section (CCS) values for multi-omic analysis.
    8 installs
20. ▌
    Post Hoc Model Interpretability 3 · holobiomicslab

    Use when after training a GNN model on molecular structures with continuous targets (e.g., CCS values), when you need to understand which node-level (atom) or edge-level (bond) features contribute most to individual or aggregate predictions.
    12 installs
21. ▌
    Basepeak Intensity Identification 2 · holobiomicslab

    Use when when you have Thermo Fisher Scientific .raw files from an Orbitrap instrument and need to identify the m/z value and corresponding intensity of the most abundant ion in each MS1 scan for quality control, method optimization, or feature extraction in a modular R-based proteomics pipeline.
    8 installs
22. ▌
    C Sharp Wrapper Method Validation 3 · holobiomicslab

    Use when when integrating an R package that wraps a compiled .NET assembly (such as rawrr), you need to verify that the internal dispatch mechanism between the R layer and the C# layer is operational before attempting to read actual raw data files.
    9 installs
23. ▌
    Calibration Curve Fitting Ms Data 3 · holobiomicslab

    Use when you have raw mass spectrometry intensity data from targeted analytes and a set of calibration standard measurements with known concentrations.
    10 installs
24. ▌
    Chemodiversity Metric Calculation 3 · holobiomicslab

    Use when when you have sum-normalized peak-abundance matrices from FT-ICR MS data with assigned molecular formulas and need to compare metabolite diversity between treatment groups (e.g., inoculated vs. control samples).
    12 installs
25. ▌
    Comparative Performance Profiling 2 · holobiomicslab

    Use when when you have implemented a new or optimized mass spectrometry data processing library and need to demonstrate its computational advantage over established alternatives (e.g., pymzML, pyOpenMS) on real proteomics data. Trigger on availability of: (1) a common input dataset (e.
    9 installs
26. ▌
    Intensity Drift Artifact Detection 3 · holobiomicslab

    Use when processing raw MS intensity tables from long measurement sequences where you observe systematic, time-dependent changes in signal magnitude (e.g., progressive increase or decrease in peak intensity across a run).
    11 installs
27. ▌
    Mass Spectrometry Benchmark Design 3 · holobiomicslab

    Use when when claiming that one mass spectrometry processing library achieves higher throughput than competitors, or when evaluating whether a new or optimized implementation delivers the expected computational efficiency gains.
    10 installs
28. ▌
    Metabolite Abundance Normalization 2 · holobiomicslab

    Use when after loading a raw metabolite abundance table (rows=metabolites, columns=samples) from Metabolomics Workbench format and before mapping metabolites to pathway identifiers or computing enrichment statistics.
    10 installs
29. ▌
    Ms Quantitative Analysis Standards 3 · holobiomicslab

    Use when you have raw MS intensity data paired with known-concentration calibration standard measurements, and you need to convert intensities to absolute or relative concentrations.
    9 installs
30. ▌
    Multi Library Comparative Analysis 3 · holobiomicslab

    Use when you need to evaluate whether a newly released or candidate library (e.g., spectrum_utils v0.4.
    8 installs
31. ▌
    Parser Error Reporting Diagnostics 3 · holobiomicslab

    Use when when implementing or extending a DSL parser (lexer + recursive descent or LALR parser) that accepts user-authored query strings.
    12 installs
32. ▌
    Pls Pls Da Classification Modeling 2 · holobiomicslab

    Use when you have a preprocessed peak table (feature matrix with samples × peaks), known sample class labels or group membership, and a goal to classify or discriminate between two or more sample groups.
    8 installs
33. ▌
    Quantitative Ms Data Preprocessing 3 · holobiomicslab

    Use when you have raw MS intensity tables showing systematic drift during a measurement sequence (e.g., declining or variable ion counts across a run), particularly in targeted quantification workflows where external calibration standards are available.
    10 installs
34. ▌
    Storage Origin Metadata Assignment 2 · holobiomicslab

    Use when when implementing or initializing an MsBackend subclass to handle mass spectrometry data, you must assign dataStorage and dataOrigin variables after loading m/z and intensity values.
    11 installs
35. ▌
    Encoder Output Dimension Reduction 3 · holobiomicslab

    Use when you have 512-dimensional representation vectors output from paired ResNet18 encoders processing augmented ion images, and you need to: (1) introduce an intermediate projection space to enable contrastive loss optimization without trivial/collapsed solutions, (2) further compress learned.
    9 installs
36. ▌
    Mass Spectrometry Peak Enumeration 2 · holobiomicslab

    Use when you have preprocessed MSI data (peaks already binned and normalized) and need to detect adduct formation patterns across the dataset.
    10 installs
37. ▌
    Molecular Structure Transformation 2 · holobiomicslab

    Use when when you have native metabolite structures (SMILES or mol format) and need to predict adduct ions for a mass spectrometry imaging experiment that uses a derivatizing matrix known to produce ions other than common [M+H]+ (positive mode) or [M-H]- (negative mode).
    7 installs
38. ▌
    Representation Collapse Prevention 3 · holobiomicslab

    Use when training a contrastive learning model on ion image data (mass spectrometry imaging) where augmented pairs of the same ion image must maximize similarity while different images minimize similarity.
    11 installs
39. ▌
    Chromatographic Peak Shape Comparison 2 · holobiomicslab

    Use when after retention-time-based and abundance-correlation-based feature grouping have produced composite feature groups, and you need to identify which features within a group actually represent different compounds.
    8 installs
40. ▌
    Extracted Ion Chromatogram Inspection 2 · holobiomicslab

    Use when after running tardisPeaks() in screening mode or peak detection mode, when you need to visually confirm that target compounds are visible in the expected m/z and retention time windows, verify that peak integration boundaries are correct, diagnose whether sawtooth artefacts are present.
    13 installs
41. ▌
    Isotope Pattern And Adduct Assignment 2 · holobiomicslab

    Use when after feature detection has produced a TSV feature table (from Asari or equivalent) containing m/z, retention time, and intensity columns, and before MS1 or MS2 annotation.
    11 installs
42. ▌
    Motif Similarity Ranking Interpretation 2 · holobiomicslab

    Use when after executing MassQL queries against a MotifDB reference database and retrieving ranked motif matches, when you need to determine which database entries represent true structural correspondence versus spurious matches, and to decide whether a motif's top-ranking hit is sufficiently.
    9 installs
43. ▌
    S4 Class Definition And Slot Management 2 · holobiomicslab

    Use when you are extending the MsBackend virtual class to create a new backend for storing MS spectra data and need to define the internal data structure. Specifically: when you have multiple types of spectra variables (e.
    9 installs
44. ▌
    Structural Cluster Network Construction 2 · holobiomicslab

    Use when after you have identified statistically significant LC-MS features and run MamsiStructSearch to generate structural clusters (isotopologue groups, adduct groups, cross-assay links) and computed correlation cluster assignments.
    8 installs
45. ▌
    Candidate Metadata Record Serialization 3 · holobiomicslab

    Use when after computing InChIKey and neighbourhood scores for library match candidates, you need to write results to a persistent format (CSV, JSON, or database) for storage, sharing, and interpretation.
    11 installs
46. ▌
    Chromatographic Modality Classification 3 · holobiomicslab

    Use when when ingesting raw or vendor-format mass spectrometry data files of unknown or mixed acquisition modality, and you need to automatically determine whether the input originated from liquid chromatography (LC), gas chromatography (GC), ion mobility spectrometry (IMS), or MS imaging (e.
    9 installs
47. ▌
    Cross Language Interface Implementation 2 · holobiomicslab

    Use when you have a mature R analysis pipeline (e.g., using Spectra objects for MS data) but need access to specialized algorithms or calculations available only in Python libraries (e.g., CosineGreedy similarity from matchms).
    11 installs
48. ▌
    Dense Neural Network Layer Construction 3 · holobiomicslab

    Use when when you have a binned MS/MS spectrum vector (e.g., 9948-dimensional input from 10,000 equally-spaced m/z bins in the 10–1000 Da range) and need to compress it into a learned latent representation (e.
    6 installs
49. ▌
    Hypergeometric Distribution Calculation 2 · holobiomicslab

    Use when when you have raw strain correlation scores (or similar overlap-based metrics) computed across genomic cluster family (GCF) and molecular family (MF) pairs of varying sizes, and you need to make those scores comparable across links with different GCF sizes (#G), MF sizes (#m), and.
    9 installs
50. ▌
    Interactive Plot Construction Mass Spec 2 · holobiomicslab

    Use when after LC-MS data has been converted to mzML format and processed through peak detection (e.g., MS-DIAL output) to yield a feature table with internal standard identifications, retention times, m/z values, and intensity measurements across multiple samples.
    10 installs
51. ▌
    Mass Spectrometry Structural Annotation 3 · holobiomicslab

    Use when after identifying statistically significant features (e.
    11 installs
52. ▌
    Mass Spectrometry Tolerance Calibration 3 · holobiomicslab

    Use when after generating a feature table from mzML data (via Asari) and before performing MS1 or MS2 annotation.
    10 installs
53. ▌
    Mass Spectrum Extraction And Formatting 4 · holobiomicslab

    Use when you have raw GC-MS data in netCDF or vendor-specific binary format and need to separate co-eluting compounds and extract clean mass spectra for each individual chemical component prior to molecular networking, spectral matching, or metabolite identification workflows.
    9 installs
54. ▌
    Ms Signal Correction Strategy Selection 2 · holobiomicslab

    Use when you have loaded raw MS intensity tables into QuantyFey and observe or suspect intensity drift artifacts across your measurement sequence. Drift is especially likely in long-running targeted MS experiments where calibration curves or internal standards show systematic variation over time.
    14 installs
55. ▌
    Natural Product Classifier Substitution 2 · holobiomicslab

    Use when gNPS has ceased supplying ClassyFire ontology information for spectral library matches, causing downstream ConCISE consensus classification to fail or produce incomplete ontology fields.
    5 installs
56. ▌
    Natural Products Workflow Orchestration 3 · holobiomicslab

    Use when you have LC-MS/MS DDA metabolomics data (positive and/or negative ionization modes) and sample metadata (originating taxon) for one or more samples, and you need to generate a Wikidata-connected RDF knowledge graph for integrated natural products analysis, taxonomy-aware compound.
    6 installs
57. ▌
    Pathway Database Filtering By Detection 2 · holobiomicslab

    Use when you have run a metabolomics experiment with incomplete coverage of a reference pathway database (e.g., 10–100% of database metabolites detected), and you plan to use ORA for pathway enrichment. The skill is essential if your detection method has known sensitivity limits (e.
    7 installs
58. ▌
    M Z Value Ordering Enforcement 2 · holobiomicslab

    Use when when implementing or modifying data replacement methods (e.g., `mz<-`, `peaksData<-`) in a writable MsBackend subclass, or when accepting user-supplied m/z vectors destined for storage in a Spectra backend.
    7 installs
59. ▌
    Mass Fragment Pattern Querying 3 · holobiomicslab

    Use when after LDA modeling has produced an inferred motifset (JSON format) containing Mass2Motifs with fragment and neutral-loss patterns.
    12 installs
60. ▌
    Mass Spectrum Peak Aggregation 2 · holobiomicslab

    Use when you have a processed mass spectrum object with assigned molecular formulas for individual peaks and need to summarize peaks by their heteroatom composition—e.
    11 installs
61. ▌
    Ms Data Constraint Enforcement 3 · holobiomicslab

    Use when implementing or validating a new MsBackend class that stores m/z and intensity values, or when assigning peak data to an existing backend. Triggers include: (1) implementing a replacement method (e.g., mz<- or intensity<-) for a backend class;
    10 installs
62. ▌
    Mzml File Format Understanding 2 · holobiomicslab

    Use when you have mass spectrometry raw data in mzML format (including compressed variants like mzML.
    11 installs
63. ▌
    Neural Network Model Inference 2 · holobiomicslab

    Use when you have pre-trained MSGO model weights (PFAS or lipid variant) and a set of experimental mass spectra (either from reference evaluation sets or real wastewater/environmental samples) in CSV format with m/z and intensity pairs, and you need to obtain candidate molecular structures ranked.
    10 installs
64. ▌
    Peak Validation Synthetic Data 2 · holobiomicslab

    Use when after running a 1D peak detection function (e.g., mzapy.peaks.find_peaks_1d_localmax or mzapy.peaks.find_peaks_1d_gauss) on synthetic mass spectra with known peak locations and heights.
    8 installs
65. ▌
    R Internal Function Invocation 3 · holobiomicslab

    Use when when you need to verify or retrieve package-internal metadata about compiled .NET assembly location and version before processing raw mass spectrometry files, or when testing the R↔C# dispatch mechanism in isolation without loading actual Orbitrap .raw data files.
    10 installs
66. ▌
    Spectral Data Table Conversion 3 · holobiomicslab

    Use when when you have mzPeak format spectrum files and need to work with spectrum metadata, intensity/m/z arrays, or precursor information in a tabular, columnar, or vectorized computing environment.
    11 installs
67. ▌
    Time Domain Signal Apodization 3 · holobiomicslab

    Use when working with raw FT-ICR transient data (e.g., ESI_NEG_SRFA.d format) prior to noise thresholding and mass-domain calibration.
    11 installs
68. ▌
    Java Build Artifact Validation 3 · holobiomicslab

    Use when when you need to verify that a Java project's automated build pipeline (GitHub Actions workflow) executes without errors and generates distributable artifacts (e.g., .deb installers, portable binaries, or .jar files).
    11 installs
69. ▌
    Matplotlib Figure Customization 2 · holobiomicslab

    Use when when rendering spectrum data (m/z vs. intensity arrays) from MZA files and need to control visual presentation: applying m/z range windows, setting line colors and labels for legend identification, sizing the figure, or choosing between interactive display versus file export.
    9 installs
70. ▌
    Metabolic Marker Identification 2 · holobiomicslab

    Use when after batch effect removal and sample integration, when you have a normalized feature-by-sample abundance matrix (finalData) with corresponding sample group labels (finalLabel), and need to identify which metabolites discriminate between biological conditions or phenotypes for focused.
    7 installs
71. ▌
    Peak Height Threshold Selection 2 · 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.
    12 installs
72. ▌
    Python Filter Class Inheritance 2 · 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.
    8 installs
73. ▌
    Spectral Data Format Validation 3 · holobiomicslab

    Use when after converting existing mass spectrometry formats (mzML, vendor formats) into mzPeak using command-line tools or when receiving mzPeak files from external sources.
    10 installs
74. ▌
    Adduct Mass Difference Matching 3 · holobiomicslab

    Use when you have computed a histogram of pairwise mass differences from MS imaging data and need to (1) identify which observed mass differences correspond to biologically relevant or chemically known adducts, or (2) rank the most frequently observed mass differences to discover dominant adduct.
    11 installs
75. ▌
    Imzml Continuous Format Parsing 2 · holobiomicslab

    Use when you have acquired raw mass spectrometry imaging data in imzML continuous format (e.g., from CardinalIO or other MSI instruments) and need to load it into R as a structured MSImagingExperiment object to perform statistical analysis, normalization, or visualization.
    11 installs
76. ▌
    Mzml To Imzml Format Conversion 2 · 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.
    12 installs
77. ▌
    Raw Vendor File Format Handling 2 · 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.
    8 installs
78. ▌
    Background Ion Contaminant Removal 2 · holobiomicslab

    Use when you have a feature table from LC-MS data alongside blank (solvent-only) sample runs, and you want to remove features whose intensity in study samples is not substantially higher than their intensity in blanks.
    9 installs
79. ▌
    Dropout Regularization Application 2 · holobiomicslab

    Use when when training a deep neural network on mass spectrometry spectral data where overfitting is a risk (especially with data augmentation applied), and when you need both regularization during training AND uncertainty quantification at inference time via multiple forward passes with dropout.
    7 installs
80. ▌
    Feature Table Row Count Validation 3 · holobiomicslab

    Use when after peak quality filtering has been applied to a composite map peak detection output using SNR (>2), goodness-of-fit (peakshape > 0.5), minimum peak height (default 1e5), and prominence (≥20% of peak_height) thresholds.
    8 installs
81. ▌
    Formula Accuracy Metric Evaluation 2 · holobiomicslab

    Use when when training or validating a deep learning model for molecular formula prediction from tandem MS/MS spectra, use this metric to track whether the model's predicted formula (including hydrogen atoms) exactly matches the annotated ground-truth formula.
    8 installs
82. ▌
    Lipid Library Format Specification 2 · holobiomicslab

    Use when when you have curated or synthesized a set of custom lipid species (e.g., rare or organism-specific lipids, modified lipids, or synthetic standards) and need to integrate them into LipidMatch for candidate matching against your experimental MS/MS datasets.
    12 installs
83. ▌
    Metabolite Set Decomposition Plage 3 · holobiomicslab

    Use when you have peak intensity data from metabolomics experiments with annotated metabolites assigned to known groupings (KEGG pathways, Reactome, GNPS Molecular Families, or MS2LDA Mass2Motifs) and need to identify which metabolite sets change significantly across experimental comparisons while.
    8 installs
84. ▌
    Metabolomics Data Input Validation 2 · holobiomicslab

    Use when when importing a tab-delimited or Sciex OS text export metabolomics dataset into mzQuality, before building the SummarizedExperiment object.
    10 installs
85. ▌
    Adduct Mass Calculation From Smiles 2 · holobiomicslab

    Use when when you have a metabolite SMILES structure and need to predict which adduct ions will appear in a mass spectrum acquired with a chemical derivatizing matrix.
    9 installs
86. ▌
    Adduct Mass Offset Parameterization 2 · holobiomicslab

    Use when when processing LC-MS metabolomics feature tables where adduct annotation is absent or incomplete, and you need to identify which ionization adducts are present in your mass spectrometry data.
    9 installs
87. ▌
    Batch Aware Normalization Workflows 2 · holobiomicslab

    Use when your LC-MS feature table exhibits intensity variations across samples that correlate with technical batches (e.
    6 installs
88. ▌
    Binary And XML Data Deserialization 2 · holobiomicslab

    Use when you have raw LC-MS data in .mzML (XML-based) or Thermo .raw (proprietary binary) format and need to load it into memory for visualization, querying, or downstream analysis.
    11 installs
89. ▌
    Chemical Class Metadata Integration 2 · holobiomicslab

    Use when you have generated a GNPS molecular network (classical or feature-based workflow) and possess chemical class annotations (from GNPS library matching, ClassyFire, or other structural classifiers) that you wish to propagate onto network nodes and edges to enable chemical family-level.
    13 installs
90. ▌
    Chemical Match Score Interpretation 3 · holobiomicslab

    Use when when you have query chemicals identified by GC-MS (with Match.Factor values) and need to verify structural similarity against a reference chemical library to confirm compound identity or detect structural analogs (e.g., isomers or homologs).
    11 installs
91. ▌
    Classification Metric Visualization 2 · holobiomicslab

    Use when after training or evaluating a classification model (e.g., a Siamese neural network for spectrum similarity prediction) and obtaining a prediction array and corresponding ground-truth label array.
    9 installs
92. ▌
    Collision Cross Section Calculation 2 · holobiomicslab

    Use when you have raw or processed arrival-time data from a traveling-wave ion mobility mass spectrometry (TWIM-MS) platform and need to convert it into standardized collision cross section (CCS) values for comparative analysis across samples or datasets.
    11 installs
93. ▌
    CSV Format Specification Compliance 2 · holobiomicslab

    Use when after feature extraction or feature alignment when you have FeatureSet or Sample objects that must be exported as CSV files for sharing, archival, or downstream analysis. Specifically: (1) when exporting single-sample feature tables from find_feature() output;
    13 installs
94. ▌
    Cytoscape Edge Node File Formatting 2 · holobiomicslab

    Use when after computing pairwise mass-difference transformations between FT-ICR MS peaks and matching them to a reference biochemical transformation key, you have putative edge data (source peak, target peak, transformation type, mass error) and node data (peaks with m/z, molecular formula.
    8 installs
95. ▌
    Dataset Preprocessing And Filtering 3 · holobiomicslab

    Use when when you have a raw GNPS or other spectral library dataset with inconsistent or incomplete instrument annotations, and you need to verify or reproduce reported dataset split counts (e.g., training/test compound ratios). Apply this skill when an instrument allowlist fix (e.
    11 installs
96. ▌
    De Novo Structure Candidate Ranking 3 · holobiomicslab

    Use when when you have high-resolution LC-MS/MS data for an unknown metabolite or small molecule, have computed or measured the molecular ion mass and fragmentation spectrum, and require de-novo structure generation because the compound is absent from spectral libraries or structure databases.
    11 installs
97. ▌
    Eic Similarity Correlation Analysis 4 · holobiomicslab

    Use when after abundance-correlation-based feature group refinement when you observe that larger feature groups (particularly those with 3+ features in the same m/z–retention-time window) may contain features with different peak shapes or retention-time shifts in their EICs, or when abundance.
    11 installs
98. ▌
    Feature Intensity Ratio Calculation 2 · holobiomicslab

    Use when after generating a feature table from LC-MS/MS data when your experiment includes blank control samples and you need to remove features driven by background ions or instrumental contamination.
    11 installs
99. ▌
    Fixed Architecture Layer Validation 3 · holobiomicslab

    Use when after loading a specXplore session data object file from the hard drive and instantiating a dashboard session layer with it, validate that the architecture layer has initialized without errors and that the interactive dashboard is responsive to user input.
    7 installs
100. ▌
     Flux Propensity Dataset Integration 2 · holobiomicslab

     Use when when you have (1) LC-MS normalized intracellular metabolite abundance data across multiple cell lines or samples, (2) a constraint-based metabolic model with stoichiometric coefficients, and (3) a need to quantify metabolic control through substrate availability independently of enzymatic.
     8 installs