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HolobiomicsLab

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1. ▌
   Transformer Encoder Architecture Implementation · holobiomicslab

   Use when when processing sequential spectroscopic data (1H NMR spectra) where both local chemical shift patterns and global spectral dependencies are needed for compound classification.
   0 installs
2. ▌
   Chromatin Accessibility Occupancy Prediction · holobiomicslab

   Use when after you have (1) corrected ATAC-seq BAM files for Tn5 insertion bias using ATACorrect, (2) computed per-base footprint scores using ScoreBigwig, (3) obtained a motif database (e.
   0 installs
3. ▌
   Configuration File Generation And Templating · holobiomicslab

   Use when when deploying a complex bioinformatics pipeline (like HiC-Pro) across heterogeneous computing environments where required tools (bowtie2, samtools, R, Python) may be installed in non-standard locations, differ in version, or require scheduler-specific configuration (TORQUE, SGE, SLURM.
   0 installs
4. ▌
   Fragment Length Estimation Cross Correlation · holobiomicslab

   Use when when beginning ChIP-Seq analysis with single-end BED/SAM input and no prior knowledge of the library's fragment length.
   0 installs
5. ▌
   Saddle Matrix Computation From Binned Tracks · holobiomicslab

   Use when you have a cooler Hi-C contact matrix file and an associated eigenvector track (from prior eigs_cis calculation or similar), and you need to quantify the preferential interaction patterns between A and B chromatin compartments.
   2 installs
6. ▌
   Acquisition Mode Enumeration And Validation · holobiomicslab

   Use when adopting a mass spectrometry-based analysis tool (e.
   1 install
7. ▌
   Adduct Annotation Against Reference Library · holobiomicslab

   Use when after computing a histogram of all pairwise mass differences from an MSI dataset, use this skill when you have observed mass difference peaks that may correspond to known adducts (e.g., [M+H]+, [M+Na]+, [M−H2O]+).
   0 installs
8. ▌
   Binary Classification Output Interpretation · holobiomicslab

   Use when you have executed a binary classifier (such as BitterPredict.m) on a set of molecules with chemical structure descriptors and need to translate the raw predictions into a structured CSV output file that maps molecule identifiers to their predicted class labels (bitter or not-bitter).
   2 installs
9. ▌
   Chemical Informatics Data Format Conversion · holobiomicslab

   Use when when you have raw SMILES strings collected from multiple external databases that require standardization and deduplication before integration into a unified chemical structure database. Specifically, apply this skill when you need to convert interim/tables/0_original/structure/smiles.tsv.
   0 installs
10. ▌
    CI CD Pipeline Reproducibility Verification · holobiomicslab

    Use when when a repository displays a GitHub Actions workflow badge (e.
    0 installs
11. ▌
    Collision Cross Section Bias Quantification · holobiomicslab

    Use when you have ion mobility-mass spectrometry lipidomics data from samples spiked with U¹³C-labeled lipid internal standards (fully labeled yeast extract) and want to assess whether measured CCS values systematically deviate from a validated DT CCS N₂ reference library, indicating bias that may.
    2 installs
12. ▌
    Count Verification Against Published Values · holobiomicslab

    Use when when you have access to a curated dataset (such as LOTUS) with published headline statistics in a peer-reviewed article or enriched index, and you need to validate data integrity, trace reporting accuracy, or establish a reproducible baseline before downstream analysis.
    0 installs
13. ▌
    Cross Language Implementation Compatibility · holobiomicslab

    Use when when a new file format specification has multiple language implementations and you need to validate that all implementations correctly interpret the specification.
    0 installs
14. ▌
    Database Schema Design For Sequential Media · holobiomicslab

    Use when when you have large sequential media files (mzML spectra, text chapters, or similar) and need to enable both random access by ID and sequential iteration without loading the entire file into memory.
    0 installs
15. ▌
    Dataframe Construction From Backend Sources · holobiomicslab

    Use when when implementing a new MsBackend subclass that stores only a subset of core spectra variables (e.
    0 installs
16. ▌
    Deep Learning Model Architecture Validation · holobiomicslab

    Use when after converting or loading a Keras model to HDF5 TensorFlow 2.3.0 format, especially when the model will be served through a pipeline (e.g., NP Classifier) that expects specific input/output layer names.
    0 installs
17. ▌
    Deep Neural Network Training Regularization · holobiomicslab

    Use when training a DNN on retention time prediction or similar continuous regression tasks where: (1) the feature space is very high-dimensional (thousands of molecular descriptors and fingerprints), (2) the training set is moderately sized (tens of thousands of molecules), (3) you observe or.
    0 installs
18. ▌
    Dotnet Framework Installation In Containers · holobiomicslab

    Use when you need to containerize a C# application (e.g., AirdPro) that targets .NET Framework 4.8 and must run on Linux hosts via Docker, but the application was originally built for Windows. Use this skill when you are building multi-stage Docker images from a Ubuntu 22.
    0 installs
19. ▌
    Linear Regression Concentration Calibration · holobiomicslab

    Use when your metabolomics experiment includes calibration line samples with known concentrations for spiked compounds, and you have computed batch-corrected compound/internal-standard ratios (ratio_corrected assay) and wish to convert relative ratios into absolute quantitative values for pathway.
    0 installs
20. ▌
    Mass Spectrometry Data Visualization Pandas · holobiomicslab

    Use when when you have mass spectrometry data (mzML, Bruker .d, or CSV) loaded into a Pandas DataFrame with columns for m/z, retention time, ion mobility, or intensity values, and you need to render spectrum plots, chromatograms, mobilograms, or 2D peak maps.
    0 installs
21. ▌
    Molecular Descriptor Fingerprint Generation · holobiomicslab

    Use when you have a collection of chemical structures (SMILES, InChI, SDF, or mol formats) and need to train or apply a machine learning model for retention time prediction or molecular property estimation.
    0 installs
22. ▌
    Molecular Formula Assignment And Validation · holobiomicslab

    Use when you have a calibrated FT-ICR transient (ESI_NEG or similar ionization mode) and need to annotate each detected m/z peak with its most likely elemental composition.
    0 installs
23. ▌
    R Dependency Package Compatibility Auditing · holobiomicslab

    Use when a Shiny application or R-based tool is known to run on only one operating system (e.g., Windows-only), and you need to identify the root causes preventing execution on Linux or macOS before undertaking cross-platform porting.
    0 installs
24. ▌
    Shiny Application Cross Platform Adaptation · holobiomicslab

    Use when when a Shiny application is documented or observed to run only on Windows, blocking deployment to Linux or macOS users. Typical triggers include hardcoded Windows path separators, unavailable packages on non-Windows systems, or system calls specific to the Windows API.
    0 installs
25. ▌
    Sonarcloud Static Code Analysis Integration · holobiomicslab

    Use when when you have a GitHub-hosted Python project (or other supported language) with an existing test suite and want to gate code contributions on multiple quality dimensions beyond unit tests—specifically when you need automated reporting of code coverage, technical debt, security issues, and.
    0 installs
26. ▌
    Application Server Datasource Configuration · holobiomicslab

    Use when when deploying a Java web application (such as CEU Mass Mediator) that requires access to a database managed outside the application server, and you have obtained database credentials from the maintainers.
    0 installs
27. ▌
    Chemical Identifier Mapping Across Services · holobiomicslab

    Use when when you have .msp files with sparse or incomplete chemical metadata (e.g., only compound names) and need to populate missing identifiers (SMILES, InChI, InChI keys, CAS numbers, IUPAC names, formulas) by querying multiple external chemical databases.
    2 installs
28. ▌
    Class Imbalance Handling In Neural Networks · holobiomicslab

    Use when your PPI prediction dataset has a large mismatch between positive (true interactions) and negative (non-interactions) labels—typical in CF-MS interactome prediction where true interactions are rare. When training an end-to-end neural network (e.
    2 installs
29. ▌
    Computational Reproducibility Documentation · holobiomicslab

    Use when when releasing or archiving a computational workflow (e.g., an R or Python-based normalization pipeline) and you need to ensure that future users or reviewers can re-run the analysis in an identical computational environment.
    1 install
30. ▌
    CSV Table Validation And Integrity Checking · holobiomicslab

    Use when you have received a raw peak table CSV (in either standardized format or output from metabolomic software tools like XCMS, MZmine, etc.) and a corresponding label file, and you need to confirm both files are well-formed and mutually consistent before passing them to NOREVA preprocessing.
    0 installs
31. ▌
    Deep Learning Model Training And Validation · holobiomicslab

    Use when you have paired mass-spectrometry spectral data (m/z and intensity arrays) with known molecular fingerprints or InChIKeys, and need to train a supervised deep learning model to predict fingerprints for novel spectra.
    0 installs
32. ▌
    Descriptive Statistics Aggregation By Group · holobiomicslab

    Use when after lipid matching is complete and you have a table of matched lipid abundances with sample annotations (e.g., experimental condition, disease state, or treatment group).
    0 installs
33. ▌
    Discrepancy Detection Threshold Calibration · holobiomicslab

    Use when normalizing metabolomics data using both QC and biological samples together.
    0 installs
34. ▌
    Distance Metric Computation Adjacency Index · holobiomicslab

    Use when you have a collection of tokenised BGCs (each gene represented as a combination of Pfam domains and subPfams) and need to identify redundant or highly similar clusters before downstream analysis.
    0 installs
35. ▌
    Domain Ontology Mapping Tcm And Ethnobotany · holobiomicslab

    Use when when integrating structure-organism pairs from TCM databases, ethnobotanical collections, or alternative medicine sources that use domain-specific or transliterated terminology (e.
    0 installs
36. ▌
    Enrichment Metric Scaling And Normalization · holobiomicslab

    Use when you have parsed GO enrichment results (CSV with GO term identifiers, p-values or adjusted p-values, gene ratios, and gene counts) and need to prepare these metrics for dotplot visualization.
    0 installs
37. ▌
    Feature Hashing Representation Mass Spectra · holobiomicslab

    Use when when you have high-resolution mass spectra that must be rapidly searched against large spectral libraries with open modifications, and you need to reduce the dimensionality of spectral data without losing the ability to retrieve spectrally similar peptides.
    0 installs
38. ▌
    Fiams Spectra Window Extraction And Merging · holobiomicslab

    Use when you have raw FIA-MS full-scan data in mzML format and need to prepare it for untargeted metabolite discovery. Apply this skill when your goal is to detect and annotate unknown metabolites across a wide m/z range (e.
    2 installs
39. ▌
    Flux Distribution Segregation Visualization · holobiomicslab

    Use when you have sampled feasible flux distributions from multiple constraint-based models (e.g., cell-line-specific variants of a metabolic model) and need to visually and quantitatively compare how well different constraint scenarios segregate biological samples.
    0 installs
40. ▌
    Ggplot2 Customization For Statistical Plots · holobiomicslab

    Use when when a statistical analysis function (e.g., random_forest or PCA_plot from Omu) returns a ggplot2 object and you need to adjust visual presentation—such as removing gridlines, applying a clean background theme (e.
    0 installs
41. ▌
    Ggplot2 Theme Customization For Publication · holobiomicslab

    Use when you have generated a ggplot2 object from a domain-specific function (e.g., omu's plot_volcano) and need to refine its appearance for publication.
    0 installs
42. ▌
    HTML Report Generation From Processed Omics · holobiomicslab

    Use when after completing batch normalization and quality control filtering on a Metaboprep object, when you need to communicate QC decisions, visualize exclusion patterns, and export final processed data for downstream analysis or sharing with collaborators.
    0 installs
43. ▌
    Ion Image Augmentation Contrastive Learning · holobiomicslab

    Use when when you have preprocessed mass spectrometry ion images (single-channel 2D arrays or multi-channel spectral images) and need to train a self-supervised encoder to learn low-dimensional representations for downstream tasks such as co-localized ion discovery (COL mode) or isotope ion.
    0 installs
44. ▌
    Ion Mobility Filtering And Tolerance Tuning · holobiomicslab

    Use when your raw MSI dataset is acquired on an ion-mobility-enabled instrument (e.g., Bruker .baf, .tsf, or .tdf formats) and your analyte of interest has a known or experimentally determined ion mobility value (1/K0 or drift time μs).
    0 installs
45. ▌
    Laser Ablation Isotope Image Interpretation · holobiomicslab

    Use when you have imported a raw LA-ICP-MS raster image (line-by-line, spot-wise, or ablation-time-aligned format) and need to isolate tissue regions from instrumental background or air before quantifying regional elemental abundance.
    0 installs
46. ▌
    Mass Spectrometry Data Object Instantiation · holobiomicslab

    Use when when you have mass spectrometry data stored in non-standard formats (SQLite, HDF5, custom binary) that pymzML does not natively support, and you want to enable random-access and sequential parsing of spectra without converting to mzML first.
    0 installs
47. ▌
    Mass Spectrometry Data Structure Conversion · holobiomicslab

    Use when when you have received metabolomics mass-spectrometry data in vendor-native or open formats (.raw, .d, mzXML) and need to ingest it into SMART for preprocessing, peak detection, or statistical analysis.
    2 installs
48. ▌
    Mass Spectrometry Quantification Extraction · holobiomicslab

    Use when you have raw LipidSearch or LIQUID output files (CSV or TSV format) containing lipid identifiers and per-sample quantification measurements, and you need to convert them into a machine-readable data matrix for downstream statistical analysis, normalization, or differential abundance.
    0 installs
49. ▌
    Mass Spectrum Scan Extraction And Windowing · holobiomicslab

    Use when when you have a full mass spectrum scan (e.g., FT1 or FT2 scan from an Orbitrap or IonTrap instrument) and need to isolate a narrow m/z window containing a known or predicted precursor ion before matching it to theoretical isotopic envelopes.
    0 installs
50. ▌
    Metabolite Column Filtering By Missing Rate · holobiomicslab

    Use when apply this filter when raw metabolomics data contains metabolite columns with varying amounts of missing values and you aim to conduct statistical analysis or imputation. The trigger is the presence of column-wise NA prevalence >10% in metabolite features;
    0 installs
51. ▌
    Metabolite Correlation Network Construction · holobiomicslab

    Use when after variance-stabilizing normalization and imputation of metabolomic data when you have a MultiAssayExperiment object containing normalized metabolite abundances and wish to identify groups of co-abundant metabolites that may share biochemical pathways or regulatory mechanisms.
    0 installs
52. ▌
    Metabolomic Data Preprocessing Optimization · holobiomicslab

    Use when you have multi-class or time-course metabolomic peak tables (with or without quality control samples and/or internal standards) and need to select the preprocessing workflow from hundreds of candidate combinations.
    1 install
53. ▌
    Metabolomics Software Build Reproducibility · holobiomicslab

    Use when when developing or maintaining a multi-platform metabolomics GUI tool (such as Maven GUI) that must produce binary executables for end users, and you need to ensure that builds are reproducible across different OS platforms, dependency versions are pinned and tracked, and release artifacts.
    0 installs
54. ▌
    Model Validation And Performance Evaluation · holobiomicslab

    Use when after training a MEISTER deep learning reconstruction model on mass spectrometry data, you must validate performance on independent test sets before applying the model to new experimental or clinical samples.
    2 installs
55. ▌
    Molecular Formula Heteroatom Classification · holobiomicslab

    Use when after molecular formula assignment has been completed on detected peaks in a processed mass spectrum object.
    0 installs
56. ▌
    Molecular Structure Representation Learning · holobiomicslab

    Use when when you have paired mass spectra and molecular structure data and need to train a model that can bidirectionally map between experimental spectra and chemical structures.
    0 installs
57. ▌
    Msi Data Visualization And Spatial Analysis · holobiomicslab

    Use when when you have imzML-format MSI data and need to identify biochemical species in specific tissue regions or anatomical structures.
    0 installs
58. ▌
    Multi Channel Image Registration Validation · holobiomicslab

    Use when after importing and manually aligning two element channels in LA-ICP-MS images, use this skill to confirm registration quality before computing spatial relationships.
    0 installs
59. ▌
    Multi Generation Transformation Hierarchies · holobiomicslab

    Use when the analytical goal requires detection of downstream transformation products that are not direct metabolites of the parent but rather products of further metabolism or degradation (e.g., secondary metabolites, conjugates of phase I products).
    0 installs
60. ▌
    Normalization Method Comparative Evaluation · holobiomicslab

    Use when you have raw metabolomics intensity data affected by batch effects and signal drift, and need to select among multiple normalization approaches based on published comparative metrics.
    0 installs
61. ▌
    Numerical Feature Serialization And Storage · holobiomicslab

    Use when after computing molecular descriptors (RDKit, mordred) or featurizing chromatographic parameters (column metadata, gradient slopes, pH, additives), you have a NumPy array or list of arrays in memory that must be persisted for reproducibility, shared across pipeline stages, or archived.
    0 installs
62. ▌
    Outlier Detection Via Multivariate Distance · holobiomicslab

    Use when after batch normalization when you have a Metaboprep object with metabolomic feature data and need to identify samples that are statistical outliers in the high-dimensional feature space. Use it when you want to detect unusual sample profiles before downstream multivariate analyses (e.
    0 installs
63. ▌
    Pearson Correlation Coefficient Computation · holobiomicslab

    Use when after annotating mass-difference pairs with candidate adduct identities, compute correlations to test whether putative parent and adduct ion intensities co-vary across the imaging pixel grid. High positive correlation (with Bonferroni-corrected p-value < 0.
    0 installs
64. ▌
    Polarity Filtering In Targeted Metabolomics · holobiomicslab

    Use when when working with targeted LC–MS metabolomics or lipidomics data where compound targets span both positive and negative ionization modes, or when your raw .
    0 installs
65. ▌
    Rt Uncertainty Quantification And Filtering · holobiomicslab

    Use when you have a set of metabolite candidates with observed retention times and access to a trained DNN retention time predictor (MAE 39.2±1.2 s) or meta-learned projections between chromatographic methods.
    0 installs
66. ▌
    Scalable Network Inference High Dimensional · holobiomicslab

    Use when when working with feature abundance tables (rows=features, columns=samples) where the feature count exceeds 10,000 and you need to infer a network of correlations between features.
    0 installs
67. ▌
    Spearman Correlation Computation Microbiome · holobiomicslab

    Use when you have cross-validated predictions of metabolite abundances from a microbiome-metabolome model and need to: (1) measure predictive accuracy at the individual metabolite level; (2) aggregate performance across all metabolites to report mean SCC;
    0 installs
68. ▌
    Spectral Feature Extraction And Integration · holobiomicslab

    Use when when you have a base message passing neural network (e.g., chemprop) trained on molecular graphs and need to augment it with infrared spectral information to improve prediction accuracy for molecular properties.
    0 installs
69. ▌
    Spectral Vector Representation And Encoding · holobiomicslab

    Use when when you have a set of mass spectra (query or library) that need to be searched against a large spectral reference database, and you want to use fast approximate nearest neighbor methods rather than exhaustive pairwise comparisons.
    0 installs
70. ▌
    Spectrum Processing Throughput Benchmarking · holobiomicslab

    Use when when selecting a spectrum processing library for high-throughput proteomics or metabolomics workflows, or when optimizing an existing pipeline for computational efficiency. Apply this skill when you have access to representative raw MS data (e.
    0 installs
71. ▌
    String Value Construction From Tabular Data · holobiomicslab

    Use when you have a JSON table (e.g., protocol records with 'type', 'id', and 'description' fields) and need to create a single concatenated string value by selecting a subset of records matching a condition (e.
    0 installs
72. ▌
    Structural Identifier Completeness Checking · holobiomicslab

    Use when preprocessing open mass spectrometry libraries (OMSLs) or aggregated spectral datasets where structural identifiers are inconsistently populated.
    0 installs
73. ▌
    Tensor Dimension Alignment And Broadcasting · holobiomicslab

    Use when when implementing a multi-task deep learning model that predicts charge, isotope count, and retention time simultaneously from mass spectrometry data, and separate feature extraction branches produce tensors of different semantic dimensions that must be integrated.
    2 installs
74. ▌
    Tool Parameter Specification And Validation · holobiomicslab

    Use when you have a working R package (e.g., IonFlow for ionomics data analysis) that performs well in standalone R environments, but need to expose it as a reusable Galaxy tool so that non-expert users can invoke it without writing R code, while preserving parameter semantics and validating input.
    0 installs
75. ▌
    Unit Test Design For Data Structure Classes · holobiomicslab

    Use when when implementing a new data structure class that extends standard Python collections (e.g., collections.UserDict) and must support multiple initialization modes, operator overloading (__add__, __sub__), custom string formatting (__str__, __repr__), and validation logic.
    0 installs
76. ▌
    Visual Pattern Recognition In Spectral Data · holobiomicslab

    Use when after database search algorithms have scored unknown MS samples against reference species, and you need to visually inspect and confirm species assignments or identify ambiguous classifications.
    0 installs
77. ▌
    CI Pipeline Reproducibility Verification · holobiomicslab

    Use when you have cloned a scientific Python project (e.g., scverse/scanpy) and need to verify that your local development environment matches the CI specification before submitting contributions, or when auditing whether the published test suite executes without failures on a fresh checkout.
    0 installs
78. ▌
    Dimensionality Reduction Via Reverse Pca · holobiomicslab

    Use when you have a normalized single-cell expression matrix (e.g., after SCTransform) and need to compute gene-level covariance structure for pathway enrichment analysis (e.g., GESECA) rather than cell-level dimensionality reduction.
    0 installs
79. ▌
    Gene Set Enrichment Scoring Coregulation · holobiomicslab

    Use when you have a normalized gene expression matrix (log2-quantile normalized, filtered to high-variance genes) and a collection of annotated gene sets (e.g., Reactome, MSigDB pathways), and need to test whether specific pathways show significant coordinated expression shifts.
    0 installs
80. ▌
    Gsea Result Interpretation Visualization · holobiomicslab

    Use when after running fgsea() on a preranked gene list when you need to: (1) identify which pathways are most significantly enriched or depleted (lowest p-values), (2) distinguish between upregulated pathways (ES > 0) and downregulated pathways (ES < 0) within your gene set collection, (3).
    1 install
81. ▌
    Hypothesis Weighting Statistical Control · holobiomicslab

    Use when when you have completed DESeq2 differential expression analysis on RNA-seq count data and obtained p-values for each gene, use IHW if you want to improve power to detect true positives beyond standard independent filtering.
    0 installs
82. ▌
    Lazy Computation Orchestration With Dask · holobiomicslab

    Use when your input is a spatial dataset (AnnData object with coordinate metadata) paired with a large tissue image, and you need to extract spatial features (via squidpy.im.calculate_image_features or similar operations) without loading the entire computation graph into memory.
    0 installs
83. ▌
    Linear Model Fitting For Gene Expression · holobiomicslab

    Use when you have a normalized gene expression matrix (genes × samples) and an experimental design with known treatment groups or conditions, and you need to estimate the effect of those conditions on expression levels while accounting for sample-to-sample variability.
    0 installs
84. ▌
    Ma Plot Visualization And Interpretation · holobiomicslab

    Use when after obtaining shrunken or unshrunken log fold change estimates from DESeq2 results objects, particularly when comparing multiple shrinkage estimator types (apeglm, normal, ashr) or evaluating the effect of shrinkage on fold change estimates across genes with varying expression levels.
    0 installs
85. ▌
    Marker Gene Identification By Clustering · holobiomicslab

    Use when you have a processed single-cell expression matrix (AnnData object) with pre-computed cluster assignments (e.g., leiden or louvain clusters in adata.obs) and want to discover which genes define each cluster's transcriptional identity.
    0 installs
86. ▌
    Memory Efficient Single Cell Computation · holobiomicslab

    Use when your input is a single-cell gene expression matrix too large to fit in RAM, or you are working in a resource-constrained environment (e.g., shared compute cluster, laptop with limited memory). You have constructed or loaded an AnnData object with X as a dask.array.
    2 installs
87. ▌
    Pathway Cell Type Association Validation · holobiomicslab

    Use when you have a multi-cluster single-cell RNA-seq dataset with cell-type annotations and you want to test whether known biological pathways (e.g., KEGG or MSigDB gene sets) show significantly elevated or differential enrichment across cell types.
    1 install
88. ▌
    Rna Seq Differential Expression Analysis · holobiomicslab

    Use when you have RNA-seq read count data (from alignment tools, transcript quantification, or feature counting) organized in a count matrix with samples as columns and genes as rows, paired with sample metadata (condition, batch, treatment), and you want to test which genes show statistically.
    0 installs
89. ▌
    Electrophoretic System Parameter Specification · holobiomicslab

    Use when you are preparing to perform effective mobility transformation of CE-MS data and must establish the electrophoretic system's calibration context.
    2 installs
90. ▌
    Ms2 Spectrum Extraction And Consensus Building · holobiomicslab

    Use when when you have DDA LC-MS/MS data (mzML format) with identified chromatographic peaks at a specific m/z (e.g., 304.1131) and multiple MS2 spectra fragmented from that precursor, and you need to produce a single high-confidence MS2 spectrum for comparison against reference databases (e.
    0 installs
91. ▌
    Chromatogram Baseline Correction Preprocessing · holobiomicslab

    Use when you have raw or folded 2D-TIC chromatogram data (typically imported from NetCDF files into RGCxGC chromatogram objects) that exhibits baseline drift, chemical noise, or instrumental artifacts that would obscure true metabolite peaks.
    0 installs
92. ▌
    Hierarchical Clustering Parameter Optimization · holobiomicslab

    Use when after peak detection in GC-IMS preprocessing, when you need to group peaks across multiple samples and must decide whether euclidean distance is appropriate for your drift time and retention time coordinate space, and when you need to validate that your chosen dt_cluster_spread_ms and.
    2 installs
93. ▌
    Mass Spectrometry Matrix Background Simulation · holobiomicslab

    Use when when you need to create negative control or background-only reference datasets for LC/GC-MS analysis pipelines—specifically to validate peak-picking algorithms, assess false-positive rates, or simulate instrument background and matrix effects (e.
    2 installs
94. ▌
    Mass Spectrometry Tolerance Window Calibration · holobiomicslab

    Use when after feature extraction from raw LC-MS or GC-MS data (using XCMS, MS-Dial, or similar), when you have a feature intensity table with m/z and RT metadata and a reference compound database (known molecules list with m/z, RT, and annotation metadata), and you need to assign confidence-ranked.
    0 installs
95. ▌
    Molecular Identifier Completeness Verification · holobiomicslab

    Use when during MSP, MGF, JSON, or CSV file parsing when standardizing mass spectra from heterogeneous open mass spectral libraries (OMSLs).
    0 installs
96. ▌
    Spectral Batch Submission To Networking Server · holobiomicslab

    Use when you have deconvolved GC-MS spectra in GNPS_GC input-compatible format and want to construct a molecular network to identify relationships between unknown compounds and perform structured chemical similarity analysis.
    0 installs
97. ▌
    Spectral Library Matching And M Z Peak Ranking · holobiomicslab

    Use when you have raw GC-MS output in CSV format (with Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, and File.Name columns) and need to systematically rank putative identifications by match quality and exact mass agreement.
    1 install
98. ▌
    Word2vec Model Inference Unknown Word Handling · holobiomicslab

    Use when when applying a pre-trained Word2Vec model to mass spectra at inference time (e.g., library matching or molecular networking), especially when the query spectra may contain fragment peaks or neutral losses not represented in the model's training vocabulary.
    0 installs
99. ▌
    Chimeric Spectra Classification Model Training · holobiomicslab

    Use when when your DDA-mode LC-MS/MS data exhibits chimeric spectra patterns that differ systematically from the reference training set used in DNMS2Purifier, or when you wish to optimize purification sensitivity/specificity for your particular instrument, ionization method, or sample matrix.
    0 installs
100. ▌
     Chromatogram And Ionization Intensity Modeling · holobiomicslab

     Use when when you need to simulate LC-MS/MS data for fragmentation strategy development and do not have (or wish to augment) real experimental chromatograms. Specifically: (1) you have a list of known or sampled chemical compounds with molecular formulae;
     2 installs