← all publishers

HolobiomicsLab

@holobiomicslab source repo

Report this profile Claim this profile

• 7.4k skills
• 0 followers
• 1 day ago last updated

1. ▌
   Message Passing Variant Selection And Adaptation · holobiomicslab

   Use when you have a baseline GNN model for predicting a continuous molecular property (e.
   0 installs
2. ▌
   Molecular Dataset Partitioning And Preprocessing · holobiomicslab

   Use when you have raw molecular datasets (e.g., METLIN-CCS, CCSBase) with SMILES strings, 3D coordinates, adduct information, and ground-truth collision cross section labels, and you need to format them for GNN training and held-out test evaluation with consistent standardization.
   0 installs
3. ▌
   Reference Dataset Validation For Metabolite Ions · holobiomicslab

   Use when after computing expected adduct ions for a metabolite using a derivatizing matrix ruleset, validate the predicted m/z values and adduct formulas against a curated reference dataset that documents which ions are actually produced by that matrix under standard ionization conditions.
   0 installs
4. ▌
   Statistical Distribution Analysis Across Cohorts · holobiomicslab

   Use when when you have prediction scores (softmax probabilities, uncertainties) from a trained deep learning model evaluated on a heterogeneous dataset and you need to determine whether prediction confidence or accuracy varies systematically across structurally distinct or novel compound.
   0 installs
5. ▌
   Command Line Tool Installation And Configuration · holobiomicslab

   Use when before launching any MetaboDirect pipeline run on a new system or environment. Trigger conditions: (1) first-time setup on a target OS (Windows, Linux, or macOS); (2) environment lacks Python 3.5+, R 4.0+, or Cytoscape 3.8+;
   0 installs
6. ▌
   Compound Class Assignment From Molecular Formula · holobiomicslab

   Use when after peaks have been filtered (by m/z, isotopic presence, and formula assignment error) and you have a list of peaks with assigned molecular formulas.
   0 installs
7. ▌
   Concentration Prediction From Calibration Curves · holobiomicslab

   Use when when you have a targeted metabolomics peak area intensity table with samples classified into calibration curve standards (with known concentration values), quality control (QC) samples, blanks, and unknowns, and you need to convert raw peak intensities into predicted concentrations for.
   0 installs
8. ▌
   Dimension Scale Linking And Cross Group Indexing · holobiomicslab

   Use when when exporting quantified MSI data as HDF5 containers following the Cardinal::HDF5 layout convention, and you need to establish bidirectional indexing between intensity data (feature-by-pixel matrix) and metadata groups (featureData, pixelData).
   0 installs
9. ▌
   Dimensionality Reduction For Batch Visualization · holobiomicslab

   Use when after data preprocessing and standardization of a metabolomics feature matrix, when you need to detect and visually characterize batch effects arising from known experimental conditions, unknown latent groups, or hidden substructures before formal statistical testing.
   0 installs
10. ▌
    Feature Intensity Preservation Across Correction · holobiomicslab

    Use when when you have loaded a raw MS quantification table (feature-by-sample intensity matrix) into QuantyFey and are applying drift-correction strategies (Internal Standard correction, statistical drift correction, Custom Bracketing, or Weighted Bracketing) but need to maintain traceability.
    0 installs
11. ▌
    Feature Table Annotation And Provenance Tracking · holobiomicslab

    Use when after generating a filtered feature table from raw mass spectrometry data in openNAU.
    0 installs
12. ▌
    Metabolite Prediction Comparison Baseline Models · holobiomicslab

    Use when you have paired microbiome (genus-level 16S or functional profiles) and metabolome datasets (e.g., mass spectrometry or metabolomics panels) with 100+ samples, and you want to demonstrate that a new prediction method outperforms prior work.
    0 installs
13. ▌
    Metabolomics Normalization Artifact Reproduction · holobiomicslab

    Use when you have raw metabolomics intensity data (rows = compounds, columns = samples) with batch annotations and QC/biological sample labels, and you need to select among five normalization methods.
    0 installs
14. ▌
    Multidimensional Feature Detection And Alignment · holobiomicslab

    Use when when you have acquired LC-IMS-MS/MS data (mzML or mzML.gz format) from multiple samples and need to detect features that exploit simultaneous separation in m/z, drift time, and retention time to improve detection sensitivity and reduce false positives.
    0 installs
15. ▌
    Peak Apex Identification From Intensity Profiles · holobiomicslab

    Use when after EIC candidate generation and peak detection have been completed on LC/HRMS data, when you need to extract the retention time and intensity values at peak maxima for each detected peak.
    0 installs
16. ▌
    Reference Peak Matching Retention Time Alignment · holobiomicslab

    Use when you have training LC-HRMS chromatograms (rt × m/z matrix format) from which you have already extracted peak candidates using smoothing and gradient-descent peak detection, and you possess a curated reference list of isolated single chromatographic peaks (ground truth).
    0 installs
17. ▌
    Regex Pattern Design For Value Format Validation · holobiomicslab

    Use when when you have a metabolomics metadata table and need to automatically identify and standardize database-ID columns (HMDB_ID, PubChem_ID, KEGG_ID, etc.) whose values follow known format conventions.
    0 installs
18. ▌
    Repository Match Consolidation And Deduplication · holobiomicslab

    Use when use this skill after parallel or sequential dispatch queries to multiple chemical repositories have returned results. Specifically: (1) you have received match records from two or more of {PubChem, ChemSpider, Norine, ChEBI, COCONUT, NP Atlas} with differing schemas or identifiers;
    0 installs
19. ▌
    Reproducibility Statistic Computation Rank Based · holobiomicslab

    Use when you have high-dimensional replicate experiment data (metabolomics, proteomics, or genomics) with multiple biological or technical replicates per sample, and you need to assess which features are reproducible across replicates and which sample pairs show consistent reproducibility patterns.
    0 installs
20. ▌
    Sample Pair Filtering By Feature Reproducibility · holobiomicslab

    Use when when you have a Marr() output object containing reproducibility statistics from replicate experiments, and your goal is to retain only those sample pairs (i,i') where reproducibility is robust across the majority of features.
    0 installs
21. ▌
    Single Cell Spatial Metabolomics Data Processing · holobiomicslab

    Use when you have raw IMC and SIMS image data from the same tissue region(s) and need to: (1) register the two modalities spatially, (2) segment individual cells across both images, (3) extract per-cell protein and metabolite intensity vectors, and (4) prepare the data for downstream joint analysis.
    0 installs
22. ▌
    Smiles Tokenization And Canonical Representation · holobiomicslab

    Use when when preparing SMILES strings as training targets for a sequence-to-sequence decoder that reconstructs molecular structures from embeddings.
    0 installs
23. ▌
    Species Authentication Classification Evaluation · holobiomicslab

    Use when when you have high-throughput mass spectrometry data (DI-MS, ASAP-MS, LDI-MS, or other ambient ionization formats) from unknown biological samples and need to determine their species identity against a curated reference database.
    0 installs
24. ▌
    Spectral Library Matching With Cosine Similarity · holobiomicslab

    Use when you have a query spectrum and a reduced candidate set of library spectra (via approximate nearest neighbor indexing), and need to search for exact unmodified peptide matches with high confidence before proceeding to variable-mass-shift modification searches.
    0 installs
25. ▌
    Missing Value Imputation For Omics · holobiomicslab

    Use when your metabolomic peak table contains missing values (e.g., undetected metabolites below instrument sensitivity or sparse measurements) and you are preparing multi-class or time-course data for statistical analysis, differential profiling, or biomarker discovery.
    0 installs
26. ▌
    Mixed Effects Model Interpretation · holobiomicslab

    Use when your metabolomics dataset contains hierarchical or repeated structure (e.g., multiple samples per batch, multiple compounds per internal standard group, or QC replicates measured across runs) and you need to model the relationship between a continuous outcome (e.
    0 installs
27. ▌
    Model Metadata Endpoint Validation · holobiomicslab

    Use when after starting a TensorFlow Serving instance (e.g., via docker-compose) and before attempting classification tasks, to confirm that input layers are named 'input_2048' and 'input_4096' and the output layer is named 'output'.
    0 installs
28. ▌
    Model Serving Artifact Preparation · holobiomicslab

    Use when you have trained Keras models that need to be deployed in a TensorFlow Serving container, and the serving infrastructure requires HDF5 TensorFlow 2.0+ format with specific input/output layer naming conventions (e.g., 'input_2048', 'input_4096', 'output').
    0 installs
29. ▌
    Module Eigenmetabolite Calculation · holobiomicslab

    Use when after metabolic correlation modules have been identified via hierarchical clustering with dynamic branch cutting on a biweight midcorrelation matrix. Apply this skill when you need a single representative abundance profile per module to correlate against sample traits (e.
    0 installs
30. ▌
    Molecular Structure Transformation · 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).
    0 installs
31. ▌
    Msi Intensity Matrix Normalization · holobiomicslab

    Use when after isotope correction when you have extracted intensity matrices from imzML or HDF5 MSI data and need to convert raw or isotope-corrected ion-image intensities into quantified values using a known internal standard lipid species.
    0 installs
32. ▌
    Msimagingarray Object Manipulation · holobiomicslab

    Use when when you have loaded mass spectrometry imaging data into a MSImagingArrays object in Cardinal 3.6 and need to explore the effects of multiple preprocessing steps (e.
    0 installs
33. ▌
    Msms Spectrum Object Instantiation · holobiomicslab

    Use when when you have successfully resolved a USI string to extract raw spectrum data from an online proteomics/metabolomics repository (PRIDE, MassIVE, etc.) and need to construct a spectrum object that exposes spectrum data as Python attributes and methods for downstream processing (filtering.
    0 installs
34. ▌
    Msp File Parsing And Serialization · holobiomicslab

    Use when you have raw .msp files containing mass spectra records and need to extract spectrum identifiers (compound name, precursor mass, retention time) as structured data for enrichment via external web services, or you have enriched spectrum objects and must write them back to .
    0 installs
35. ▌
    Multi Source Metabolite Resolution · holobiomicslab

    Use when you have metabolite identifiers sourced from a single metabolome database (e.
    0 installs
36. ▌
    Multi Task Learning Feature Fusion · holobiomicslab

    Use when when you have multi-branch deep learning architecture predicting related but distinct peptide properties (charge state, isotope count, retention time) from raw mass spectrum, and you want to leverage auxiliary task gradients to improve primary task learning.
    0 installs
37. ▌
    Natural Product Structure Encoding · holobiomicslab

    Use when you have natural product molecules in SMILES, InChI, or SDF format and need to convert them into fixed-length numerical feature vectors for downstream machine learning tasks (e.g., biosynthetic class prediction, molecular similarity analysis, or chemical space exploration).
    0 installs
38. ▌
    Network Layout Algorithm Selection · holobiomicslab

    Use when you have a network object (nodes and edges) loaded in MetaNet and need to compute 2D or 3D spatial coordinates for visualization. This skill is necessary before any network plotting step. Choose this when your network structure (e.
    0 installs
39. ▌
    P Value Cutoff Threshold Filtering · holobiomicslab

    Use when after differential expression analysis (DEA) has produced p-values and log fold-change values for multiple omics layers (genes, miRNA, proteins, lipids), and you need to select only statistically significant features for pathway enrichment.
    0 installs
40. ▌
    Pathway Kernel Association Testing · holobiomicslab

    Use when you have paired genotype and phenotype data and want to test for association between a predefined genetic pathway (set of genes or variants) and a quantitative or binary trait, particularly when individual-variant tests lack power or when pathway-level aggregation is scientifically.
    0 installs
41. ▌
    Peak Detection Accuracy Assessment · holobiomicslab

    Use when after running a non-targeted preprocessing (NPP) pipeline (e.g., XCMS, MZmine 2, OpenMS) on the same set of centroided mzML files that were used to generate a validated benchmark dataset.
    0 installs
42. ▌
    Peak Filtering And Quality Control · holobiomicslab

    Use when after peak picking and alignment have been performed on MSImagingArrays data (via peakPick() and peakProcess()), apply this skill when you need to remove noise-driven or low-frequency peaks before summarizing reference peaks across the full imaging dataset.
    0 installs
43. ▌
    Plant Nomenclature Standardization · holobiomicslab

    Use when when your metadata table contains species, genus, or family names that may be outdated, synonymous, or non-canonical, and you need to integrate them with the Literature Component (which requires standardized taxon identifiers) or cross-reference with external databases like Lotus Database.
    0 installs
44. ▌
    Pls Pls Da Classification Modeling · 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.
    0 installs
45. ▌
    Positional Encoding Implementation · holobiomicslab

    Use when you need to feed discrete chemical formula representations (e.g., 'C6H12O6') into a neural network that requires continuous vector inputs, particularly when adopting a transformer architecture for formula ranking or property prediction tasks.
    0 installs
46. ▌
    Precision Matrix Network Inference · holobiomicslab

    Use when you have a feature matrix (rows=samples, columns=features) and need to infer conditional independence structure among features, particularly when the true network is believed to be sparse and you want to control the sparsity level via regularization.
    0 installs
47. ▌
    Psm Rank Filtering Input Selection · holobiomicslab

    Use when you have a PSM file from a proteomics search engine containing multiple candidate identifications per spectrum and need to prepare input for rescoring with MS²Rescore. Use it when computational resources are limited or when you want to focus rescoring on high-confidence candidates (e.
    0 installs
48. ▌
    Psm To Spectrum Linking Validation · holobiomicslab

    Use when when you have PSM files from a proteomics search engine (e.g., MaxQuant, MSGFPlus, Mascot) and corresponding spectrum files (mzML or MGF format) that need to be linked before rescoring.
    0 installs
49. ▌
    Python Binary Io And Serialization · holobiomicslab

    Use when when you have mzPeak files (Parquet-based archives in uncompressed ZIP containers) or other PyArrow-compatible columnar formats containing mass spectrometry spectra, and you need to extract and decode spectral data arrays (m/z values, intensities) into Python memory for downstream.
    0 installs
50. ▌
    Qc Dilution Consistency Validation · holobiomicslab

    Use when after CV-based and blank-contribution filtering when you have untargeted metabolomics feature tables with QC samples that include dilution series (QC_half) and you need to ensure features exhibit consistent, approximately proportional intensity changes across dilution steps.
    0 installs
51. ▌
    Quantification Table Normalization · holobiomicslab

    Use when you have raw quantification data (abundance or intensity values across samples and features) from mass spectrometry or similar high-dimensional assays and need to prepare it for msFeaST's feature selection workflow, which requires standardized internal data structures compatible with.
    0 installs
52. ▌
    Quantile Normalization Application · holobiomicslab

    Use when after autoQ has extracted peak area measurements for isotopologues from GC-CI-MS data and you need to prepare these integrations for barplot visualization with metBarPlot.
    0 installs
53. ▌
    Queued Spectrum Preview Generation · holobiomicslab

    Use when when you have queued one or more spectral processing operations (e.g., smooth(), normalize(), reduceBaseline()) on an MSImagingArrays object and need to inspect the effect on representative spectra before processing the full dataset.
    0 installs
54. ▌
    R Ggplot2 Multi Dimension Encoding · holobiomicslab

    Use when when you have tabular GO enrichment or gene set analysis results with at least 3–4 quantitative or categorical dimensions (e.
    0 installs
55. ▌
    R Internal Function Implementation · holobiomicslab

    Use when you need to expose capabilities of an external compiled dependency (e.g., a .NET assembly, C# wrapper, or executable) to R code, but direct R bindings do not exist.
    0 installs
56. ▌
    R Python Interoperability Bridging · holobiomicslab

    Use when when your analysis requires functionality from both R (statistical modeling, ROC analysis, caret machine learning) and Python (keras deep learning backend, numpy arrays) within a single R session, particularly for cross-language machine learning workflows like SERDA normalization that.
    0 installs
57. ▌
    R Script Configuration And Editing · holobiomicslab

    Use when you need to switch between Modular and Flow execution modes in LipidMatch/FluoroMatch, or when you need to change the analysis application type (PFAS analysis, Lipid analysis, or TWeen_pos analysis).
    0 installs
58. ▌
    R Script Execution And Integration · holobiomicslab

    Use when when you have pre-written R functions organized across multiple .R files (e.g., GSimp.R, GSimp_evaluation.R, Impute_wrapper.
    0 installs
59. ▌
    Recursive Algorithm Implementation · holobiomicslab

    Use when after peak detection on LC/HRMS data (mzXML, mzML, netCDF formats) when m/z values require refinement for improved mass accuracy in untargeted metabolomics workflows.
    0 installs
60. ▌
    Relative Log Abundance Calculation · holobiomicslab

    Use when after applying a normalization method (e.g., median scaling, RUV, RLSC) to metabolomics peak intensity data, when you need to visually assess whether normalization has successfully reduced batch effects and whether samples cluster appropriately by biological group.
    0 installs
61. ▌
    Repository Code Quality Assessment · holobiomicslab

    Use when you need to validate that all Python files in a repository meet the project's stated code formatting and style guidelines before merging a pull request, onboarding a new contributor, or establishing a baseline for code quality.
    0 installs
62. ▌
    Sample Group Injection Aggregation · holobiomicslab

    Use when when you have picked and annotated MS1 features from replicate injections of the same sample and need to produce a unified feature matrix indexed by sample (not injection).
    0 installs
63. ▌
    Saturation Threshold Configuration · holobiomicslab

    Use when when executing peak integration on preprocessed GC-IMS data (after alignment and baseline correction) and you need to decide whether to include or exclude peaks that exhibit saturation artifacts from the RIP signal. Set a threshold (e.g., 0.
    0 installs
64. ▌
    Seed Product Relationship Tracking · holobiomicslab

    Use when when applying biotransformation rules to seed metabolites to generate candidates, you need to record which rule produced each candidate and link it back to its parent seed structure. This is essential for downstream validation (e.
    0 installs
65. ▌
    Shiny App Configuration Deployment · holobiomicslab

    Use when you have built a Shiny application (global.R, ui.R, server.
    0 installs
66. ▌
    Side Chain Representation Learning · holobiomicslab

    Use when working with natural product molecules where conventional synthetic-molecule representations fail to capture synthesis patterns, and you need to encode both scaffold topology and the diverse chemical substituents (side chains) that distinguish natural product variants.
    0 installs
67. ▌
    Smiles Structure Format Validation · holobiomicslab

    Use when when you have raw molecular structures in SMILES or .sdf format and need to feed them into CypReact for CYP isoform prediction. Apply this skill before invoking the CypReact command-line tool to avoid runtime failures due to malformed input.
    0 installs
68. ▌
    Spatial Pixel Coordinate Alignment · holobiomicslab

    Use when you have mzML files from a mass spectrometry imaging (MSI) experiment and need to convert them to imzML format with correctly positioned pixel coordinates.
    0 installs
69. ▌
    Spatio Molecular Matrix Processing · holobiomicslab

    Use when you have deposited SpaceM spatio-molecular matrices (MORPHnMOL.
    0 installs
70. ▌
    Spectra Variable Metadata Handling · holobiomicslab

    Use when when designing a new MsBackend subclass or extending an existing backend to support mass spectrometry data import or representation.
    0 installs
71. ▌
    Spectral Search Result Aggregation · holobiomicslab

    Use when when you have executed batch searches of MS/MS spectra against multiple domain-specific MASST indices and need to consolidate results across domains (e.
    0 installs
72. ▌
    Storage Origin Metadata Assignment · 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.
    0 installs
73. ▌
    System Configuration Documentation · holobiomicslab

    Use when after successfully installing and validating all components of a complex multi-tool workflow (such as ENPKG), when you have confirmed that all dependencies resolve, external tools (e.g., Sirius, MZmine) are accessible at their expected paths, and test commands execute without error.
    0 installs
74. ▌
    T Test Interpretation Metabolomics · holobiomicslab

    Use when you have preprocessed, normalized, and imputed metabolite measurements organized in a MultiAssayExperiment object with two or more clearly defined sample groups (e.
    0 installs
75. ▌
    Table Record Filtering And Sorting · holobiomicslab

    Use when you have a table with multiple records (e.g., a protocol table with type, id, and description fields) and need to extract a subset of records matching a specific field criterion (e.
    0 installs
76. ▌
    Taxonomy Classification Evaluation · holobiomicslab

    Use when you have a pre-trained model (or candidate models) and need to assess whether it generalizes better than existing synthetic-molecule baselines on natural product taxonomy classification.
    0 installs
77. ▌
    Test Driven Development Validation · holobiomicslab

    Use when when you have implemented or modified a bioinformatic fingerprint generation function (or similar molecular computation module) and need to verify that: (1) the function accepts the correct input types (molecule objects from RDKit or equivalent), (2) it produces fixed-length numerical.
    0 installs
78. ▌
    Toml Configuration File Generation · holobiomicslab

    Use when when beginning a LipoCLEAN analysis workflow and needing to configure MS-DIAL export file locations, filtering parameters, and other tool options. Specifically when you have MS-DIAL 4 or MS-DIAL 5 exported data and need to prepare an options.txt file before running lipid quality filtering.
    0 installs
79. ▌
    Transfer Learning Model Adaptation · holobiomicslab

    Use when you have a pre-trained ABCoRT model checkpoint and a new chromatography dataset (e.g., Eawag_XBridgeC18_364.
    0 installs
80. ▌
    Unsaturation Degree Quantification · holobiomicslab

    Use when you have FT-ICR MS peak data with assigned molecular formulas (C, H, O, N, S, P elemental counts) and want to characterize the structural saturation and aromaticity of metabolites to assess their biochemical degradation potential, compare chemodiversity across samples, or stratify.
    0 installs
81. ▌
    User Override Parameter Management · holobiomicslab

    Use when punc'data's automatic keyword-based column recognition produces incorrect semantic role assignments—for example, when a column header contains a non-standard keyword that the tool fails to recognize, or when a column's true semantic role (e.
    0 installs
82. ▌
    Wine Windows Runtime Configuration · holobiomicslab

    Use when you have a Windows-only C# GUI application (e.g., AirdPro) built for .NET Framework 4.8 that needs to run on non-Windows hosts (macOS or Linux), and you are using a multi-stage Docker build where the runtime stage includes Wine and Windows compatibility libraries.
    0 installs
83. ▌
    Ms Imaging Spatial Metabolomics Workflow · holobiomicslab bundle

    Use when you have mass-spectrometry imaging data (imzML, e.g. MALDI/DESI) and want spatially-resolved metabolite annotations — pixel preprocessing and m/z alignment, FDR-controlled spatial annotation, spatial segmentation, and region-wise comparison.
    0 installs
84. ▌
    Bayesian Effect Size Moderation · holobiomicslab

    Use when after running DESeq2 differential expression analysis and extracting results with raw log fold changes, apply this skill when you observe high variance in effect size estimates across genes—particularly when many genes have small counts, unreliable variance estimates, or when you want.
    0 installs
85. ▌
    Gene Expression Linear Modeling · holobiomicslab

    Use when you have normalized or voom-transformed gene expression counts/intensities indexed by gene and sample, along with an experimental design matrix specifying condition, batch, or covariate assignments.
    0 installs
86. ▌
    K Mer Orientation Bug Diagnosis · holobiomicslab

    Use when a Rust port or alternative implementation of a mapper (e.g., salmon, piscem) consistently maps 2–3% more reads than a C++ reference, especially on short reads.
    0 installs
87. ▌
    Pathway Set Enrichment Analysis · holobiomicslab

    Use when you have normalized gene expression data (log-transformed, quantile-normalized) from a time-course or case-control experiment, a ranked gene statistic (e.g., mean expression, differential expression score), and a collection of curated gene sets (e.
    0 installs
88. ▌
    Rna Seq Count Matrix Generation · holobiomicslab

    Use when you have transcript-level abundance estimates from salmon, sailfish, or kallisto quantification and need gene-level count matrices for differential expression analysis.
    0 installs
89. ▌
    Rna Seq Count Normalization Tmm · holobiomicslab

    Use when apply TMM normalization when you have raw RNA-seq read counts from multiple samples and suspect differences in library composition (e.g., one sample over-represents a highly-expressed gene or transcript class relative to others).
    0 installs
90. ▌
    Bioconductor Data Import And Handling · holobiomicslab

    Use when you have CE-MS test files archived in the msdata Bioconductor package and need to load them into an in-memory or on-disk R representation to extract ion electropherograms, pick peaks, or compute effective mobility transformations.
    0 installs
91. ▌
    Mass Spectrum Fragment Ion Extraction · holobiomicslab

    Use when you have an experimental MS/MS spectrum (e.g., from MassBank or acquired data) for a single metabolite with known accurate precursor m/z and adduct type, and you need to generate a library entry with scored fragments for use in metabolite annotation pipelines.
    0 installs
92. ▌
    Normalization For Unequal Group Sizes · holobiomicslab

    Use when when tabulating chemical annotation enrichment (e.g., GNPS spectral library matches) across sample groups stratified by metadata category (e.g., sample type, extraction method, ionization source), and the groups contain different numbers of files or samples.
    0 installs
93. ▌
    Compound Data Subsetting By Threshold · holobiomicslab

    Use when you have a GC-MS dataset with a Match.Factor column (or equivalent quality metric) and need to evaluate how many unique compounds are retained at different confidence thresholds, or when you must subset the compound list to a user-defined quality level before downstream cheminformatics.
    0 installs
94. ▌
    Concentration Matrix Estimation Gc Ms · holobiomicslab

    Use when after GCMSFormer (or similar Transformer model) has predicted pure mass spectra (matrix S) for all components in overlapped GC-MS peaks, apply this skill to quantify the relative abundance of each component.
    0 installs
95. ▌
    Corpus Size Coverage Scaling Analysis · holobiomicslab

    Use when when deploying a Word2Vec-based spectral similarity model (such as Spec2Vec) on a new mass spectrometry dataset and needing to assess whether the pre-trained model's learned peak embeddings sufficiently represent the peaks in your query spectra.
    0 installs
96. ▌
    Cosine Similarity Spectral Clustering · holobiomicslab

    Use when you have a collection of deconvolved mass spectra (in MGF or mzTab format) from GC-MS analysis and need to group them into a molecular network to identify structural relationships and enable compound annotation.
    0 installs
97. ▌
    Gaussian Peakshape Fitting Evaluation · holobiomicslab

    Use when after peak detection on mass track segments using find_peaks, when you need to distinguish genuine chromatographic peaks from noise-induced false positives or irregular shapes.
    0 installs
98. ▌
    Mass Spectrometry Compound Extraction · holobiomicslab

    Use when you have a preprocessed GC-MS dataset (from spreadOut) with standardized column names (Compound.Name, Component.RT, Base.Peak.MZ, Component.Area, Match.Factor) and a specific list of chemical compounds you want to extract and aggregate across multiple sample runs.
    0 installs
99. ▌
    Mass Spectrometry Screening Workflows · holobiomicslab

    Use when when you have high-resolution LC-MS or GC-MS data from environmental samples and need to simultaneously screen for both known suspect chemicals and their transformation products, rather than targeting single compounds.
    0 installs
100. ▌
     Metabolite Tandem Ms Library Curation · holobiomicslab

     Use when you have multiple tandem MS/MS libraries in different formats (msp, mgf) from different providers (NIST, RIKEN, MoNA, GNPS) with incomplete or inconsistent structural annotations (missing SMILES or molecular formula fields) and need to combine them into unified, polarity-specific msp files.
     0 installs