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HolobiomicsLab

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1. ▌
   Chromatographic Peak Detection And Integration · holobiomicslab

   Use when after loading centroided .mzML LC-MS data and defining a target list (compound ID, name, m/z, RT, polarity) when you need to: (1) automatically locate and integrate peaks for known compounds across multiple runs; (2) generate per-target and per-run quantitative metrics;
   0 installs
2. ▌
   Chromatographic Peak Quality Metric Evaluation · holobiomicslab

   Use when when processing untargeted LC-MS metabolomics data with XCMS and need to identify low-quality peak integrations that may introduce noise or bias into subsequent compound identification and quantification.
   2 installs
3. ▌
   Contrastive Learning For Cross Modal Retrieval · holobiomicslab

   Use when you have paired MS/MS spectra and molecular structures (SMILES or SDF format) and need to perform compound identification by retrieving the correct structure for an unknown spectrum.
   2 installs
4. ▌
   Distribution Shape Adaptation In Normalization · holobiomicslab

   Use when after imputation and correction, when metabolomic feature intensities exhibit heteroscedastic variance or non-normal distributions across samples.
   0 installs
5. ▌
   Domain Specific Spectrum Search Implementation · holobiomicslab

   Use when you have acquired one or more tandem MS/MS spectra and need to identify metabolites against a reference library filtered by biological domain (e.
   0 installs
6. ▌
   Feature Abundance Pattern Correlation Analysis · holobiomicslab

   Use when after initial retention-time-based feature grouping has been performed on LC-MS data but before final EIC similarity refinement.
   2 installs
7. ▌
   Feature Annotation Via Isotope Adduct Grouping · holobiomicslab

   Use when after peak detection and feature extraction have produced a composite feature table with m/z, retention time, and intensity values for individual samples.
   0 installs
8. ▌
   Feature Based Molecular Network Interpretation · holobiomicslab

   Use when you have a feature-based molecular network generated from non-targeted LC-MS/MS metabolomics data (e.
   2 installs
9. ▌
   Feature Quality Assessment By Rsd Within Class · holobiomicslab

   Use when after blank subtraction and background drift removal in an MS-DIAL peak list, when you need to exclude features with high within-class measurement variability. Apply this when you have replicate samples assigned to distinct classes (e.
   0 installs
10. ▌
    Feedforward Neural Network Architecture Design · holobiomicslab

    Use when you have preprocessed molecular structures as fixed-length feature vectors and need to establish a fair-comparison baseline model for tandem mass spectrum prediction.
    0 installs
11. ▌
    Intensity To Absolute Concentration Conversion · holobiomicslab

    Use when your lipidomics experiment includes spiked internal lipid standards of known concentration, and you have raw signal intensity matrices from LipidSearch or LIQUID output.
    0 installs
12. ▌
    Lipid Fingerprint Regeneration Neural Networks · holobiomicslab

    Use when you have MS/MS spectra with initial lipid annotations from spectral library matching (e.g., from XCMS + CAMERA or LipidIN's Expeditious Querying module) and seek to improve recall, precision, and annotation coverage.
    0 installs
13. ▌
    Machine Learning Performance Metric Evaluation · holobiomicslab

    Use when after training a binary MS/MS spectral classifier on labeled data, apply this skill to quantify classifier performance before deployment.
    2 installs
14. ▌
    Mass Spectra Clustering Hyperdimensional Space · holobiomicslab

    Use when you have large-scale MS/MS spectra datasets (hundreds of thousands to millions of spectra) in MGF format that need to be grouped by similarity, and you have access to NVIDIA GPU hardware (GTX 1080Ti or GTX 3090).
    0 installs
15. ▌
    Mass Spectrometry Peak Alignment Visualization · holobiomicslab

    Use when when you have aligned peak data from molecular networking (with m/z, intensity, retention time, and alignment quality metrics across multiple spectra) and need to interactively explore peak alignments under multiple filtering criteria (intensity thresholds, alignment score cutoffs, peak.
    0 installs
16. ▌
    Mass Spectrometry Reference Standard Alignment · holobiomicslab

    Use when you have positive- or negative-mode tunemix reference data (with known CCS values, m/z, and measured drift times) and need to establish a calibration model for converting observed drift times into CCS values for downstream feature annotation.
    0 installs
17. ▌
    Monte Carlo Dropout Uncertainty Quantification · holobiomicslab

    Use when when a trained Siamese neural network model makes predictions on new spectrum pairs and you need to identify and exclude high-uncertainty predictions to improve RMSE.
    2 installs
18. ▌
    Ms Ms Spectral Preprocessing And Normalization · holobiomicslab

    Use when you have a labelled dataset of raw MS/MS spectra annotated as 'relevant' (compounds of interest) or 'other' (reference standards or non-target compounds) and need to prepare them for supervised classifier training.
    2 installs
19. ▌
    Ms Ms Spectrum Tokenization And Representation · holobiomicslab

    Use when when you have raw MS/MS spectra in MSP format (or similar) with m/z–intensity peak pairs and need to prepare them for neural embedding models that require fixed-size discrete token inputs. Applies before generating dense spectral embeddings for retrieval or similarity scoring tasks.
    2 installs
20. ▌
    Multi Assay Data Integration And Harmonization · holobiomicslab

    Use when you have independent LC-MS assays (e.g., positive and negative ionization modes, different lipid profiling assays, or different chromatographic methods) analyzed on the same sample cohort and want to integrate them into a single discriminant or regression model without losing assay-level.
    0 installs
21. ▌
    Multi Window Mass Range Parameter Optimization · holobiomicslab

    Use when you observe sawtooth or discontinuous peak profiles in EICs after running tardisPeaks() on LC-MS data acquired with multiple overlapping or sequential m/z scan windows (e.g., positive and negative polarity scans, or data-independent acquisition with staggered windows).
    0 installs
22. ▌
    Multiplexed Spectra Recovery And Deconvolution · holobiomicslab

    Use when you have raw IM-MS data in UIMF or Agilent MassHunter .d format acquired from a multiplexed (interleaved) ion mobility experiment, and you need to recover individual, demultiplexed frames to reconstruct conventional IM-MS spectra for downstream omics analysis.
    1 install
23. ▌
    Multivariate Statistical Analysis Metabolomics · holobiomicslab

    Use when when you have preprocessed non-targeted LC-MS/MS feature tables (post-merging, cleanup, blank removal, and batch correction) and seek to uncover multivariate patterns across samples, discriminate between experimental groups, or reduce dimensionality of high-dimensional metabolomic data.
    0 installs
24. ▌
    Nearest Neighbor Clustering By Mass Difference · holobiomicslab

    Use when processing LC-MS metabolomics studies with >10 samples where sample count and memory constraints make pairwise mass alignment infeasible.
    2 installs
25. ▌
    Network Component Identification And Filtering · holobiomicslab

    Use when you have a GNPS GraphML molecular network and need to isolate cohesive subsets of spectra (components) before analyzing which fragmentation patterns explain them.
    0 installs
26. ▌
    Neural Network Layer Design And Implementation · holobiomicslab

    Use when when replacing deprecated model components (e.
    0 installs
27. ▌
    Peak Map Rendering Retention Time Mz Intensity · holobiomicslab

    Use when when you have loaded mass spectrometry data (from mzML or Bruker .
    0 installs
28. ▌
    Peak Neutral Loss Occurrence Data Manipulation · holobiomicslab

    Use when you have aligned MS2 spectra from multiple samples and need to create a matrix representation where rows are samples and columns are MS2 peaks or neutral losses (mass differences to the precursor), with counts of occurrences.
    0 installs
29. ▌
    Percentile Feature Filtering For Normalization · holobiomicslab

    Use when you have a raw or pre-processed LC-MS feature table with multiple samples and need to normalize for inter-sample intensity biases before downstream statistical analysis.
    0 installs
30. ▌
    Performance Benchmarking Computational Systems · holobiomicslab

    Use when you have implemented or reconstructed a performance-critical computational module (e.g., an expeditious querying engine, a database lookup accelerator, or a real-time matching algorithm) and need to validate that it achieves claimed throughput targets.
    0 installs
31. ▌
    Probabilistic Topic Modeling Mass Spectrometry · holobiomicslab

    Use when you have preprocessed tandem mass spectrometry spectra converted into a bag-of-fragments representation (with fragments and neutral losses extracted and noise filtered) and your goal is to discover recurring fragmentation patterns or substructures across a large spectral dataset without.
    2 installs
32. ▌
    Python Class Interface Design For Ml Libraries · holobiomicslab

    Use when when building a machine learning library for scientific workflows where users need to: (1) prepare domain-specific data (e.
    0 installs
33. ▌
    Resolution Effect Correction Unlabeled Samples · holobiomicslab

    Use when when you have paired LC-MS data from both labeled (isotope-tracer dosed) and unlabeled (control) samples of the same analytes, and you want to correct FAM to true MDV while accounting for resolution effects from the mass spectrometer (especially relevant for high-resolution instruments.
    4 installs
34. ▌
    Retention Time Regression Output Specification · holobiomicslab

    Use when after initializing and executing a forward pass through a dual-branch RT-Transformer model (combining fingerprint and molecular graph inputs) on a batch of molecular samples, to verify that the output tensor conforms to the expected shape, data type, and numeric range for retention time.
    1 install
35. ▌
    Ribosomally Synthesized Peptide Identification · holobiomicslab

    Use when you have LC-MS/MS spectral data (in MGF, mzXML, mzML, or mzData format) and corresponding genomic sequence data (raw FASTA nucleotide sequences or genome mining tool outputs like antiSMASH .final.
    2 installs
36. ▌
    Selectivity Metric Computation Chromatographic · holobiomicslab

    Use when after peak detection on composite mass tracks when you need to evaluate whether a detected peak represents a pure, interference-free signal on its m/z channel.
    1 install
37. ▌
    Source Code Inspection For Preprocessing Steps · holobiomicslab

    Use when when you need to verify that a specific data transformation (e.g., precursor m/z zeroing, feature scaling, or field masking) is applied consistently across multiple execution workflows (training, evaluation, inference) in a codebase.
    0 installs
38. ▌
    Spectral Denoising Via Training Data Filtering · holobiomicslab

    Use when you have untargeted MS2 spectra from environmental or clinical samples that will be used for natural product identification (e.g., linking to BGCs via IOKR or other kernel-based methods), and you have access to a high-quality training library of annotated spectra with known structures.
    0 installs
39. ▌
    Spectral Format Conversion Mzml To Proprietary · holobiomicslab

    Use when after clustering features with RAMClustR and inferring molecular weights via do.findmain, when you need to perform structure elucidation or molecular formula prediction using MSFinder (for .mat format) or Sirius (for .ms format).
    0 installs
40. ▌
    Spectral Peak Frequency Threshold Optimization · holobiomicslab

    Use when you have MS/MS spectra with fragment frequency annotations (from consensus spectrum generation) and need to decide which fragments to retain versus remove. Trigger conditions: (1) you have replicate MS/MS spectra for the same feature with per-fragment recurrence frequencies calculated;
    0 installs
41. ▌
    Spectral Similarity Prediction Neural Networks · holobiomicslab

    Use when when you have paired MS/MS spectra with known structural similarity labels (Tanimoto scores from molecular fingerprints) and need to predict structural similarity for new spectrum pairs faster than fingerprint-based methods, or when you want to assess model prediction confidence per.
    0 installs
42. ▌
    Spectrum Preprocessing For Similarity Analysis · holobiomicslab

    Use when when you have raw MS/MS spectra with residual noise or low-intensity peaks and plan to calculate spectral entropy, entropy similarity, or perform spectral library matching.
    0 installs
43. ▌
    Statistical Hypothesis Testing Mean Comparison · holobiomicslab

    Use when you have computed raw or standardised correlation scores (or other link-ranking metrics) for all possible GCF-MF pairs in a dataset and want to verify that validated links (those with known strain co-occurrence or experimental confirmation) are significantly enriched at higher score values.
    0 installs
44. ▌
    Tandem Mass Spectrum Prediction Fragment Level · holobiomicslab

    Use when you have a molecular structure (SMILES, InChI, or chemical formula) and need to predict its collision-induced dissociation (CID) tandem mass spectrum with fragment-level resolution. Use this when chemical-formula-level predictions (e.
    0 installs
45. ▌
    Technical Replicate Reproducibility Assessment · holobiomicslab

    Use when you have tandem MS data with technical replicates and need to remove features showing high variability between replicates.
    0 installs
46. ▌
    Thermo Fisher Orbitrap Metadata Interpretation · holobiomicslab

    Use when when you have a Thermo Fisher Scientific .
    0 installs
47. ▌
    Univariate Statistical Analysis Interpretation · holobiomicslab

    Use when you have a preprocessed feature table from non-targeted LC-MS/MS metabolomics data (after data merging, cleanup, blank removal, and batch correction) and need to test whether individual metabolomic features show statistically significant differences between experimental groups or.
    1 install
48. ▌
    Untargeted Metabolomics Feature Interpretation · holobiomicslab

    Use when you have an untargeted metabolomics feature table (m/z values, retention times, p-values from statistical testing) and need to infer which metabolic pathways are active without performing metabolite identification.
    2 installs
49. ▌
    Cohort Stratified Metabolic Performance Analysis · holobiomicslab

    Use when when you have uploaded a pre-analytical data table containing sample metadata, processing delay annotations (pre- and post-centrifugation times), and paired NMR metabolomic measurements for a plasma or serum cohort, and you need to determine how processing delays impact metabolite.
    0 installs
50. ▌
    Heteronuclear Homonuclear Correlation Extraction · holobiomicslab

    Use when you have 2D NMR spectral data from multiple samples (a large sample set) including both heteronuclear experiments (HSQC, HMBC) and homonuclear experiments (COSY), and your goal is to identify which structural features are conserved across samples, prioritize samples by scaffold similarity.
    2 installs
51. ▌
    Nmr Spectra Preprocessing And Feature Extraction · holobiomicslab

    Use when when you have raw or lightly processed 1D NMR spectra (¹H and/or ¹³C) from unknown organic compounds and need to extract latent spectral features prior to structure elucidation.
    0 installs
52. ▌
    Python Deep Learning Model Loading And Execution · holobiomicslab

    Use when when you have a pre-trained deep learning model checkpoint (saved in PyTorch format) and new 1D 1H NMR spectral data in CSV and peak-list TXT formats, and you need to generate peak-to-metabolite assignments or other structured outputs from that model without modification of model weights.
    0 installs
53. ▌
    Spectral Visualization And Result Interpretation · holobiomicslab

    Use when after peak clustering, network filtering, and database matching have identified candidate metabolites and their associated peak networks.
    0 installs
54. ▌
    Chromatin Accessibility Deviation Computation · holobiomicslab

    Use when when you have filtered ATAC-seq or DNAse-seq peak counts (after GC bias correction, sample filtering, and peak filtering) and wish to measure how strongly each annotation (motif or kmer) influences chromatin accessibility variability in each sample relative to a background expectation.
    0 installs
55. ▌
    Library Module Organization And Accessibility · holobiomicslab

    Use when you are building or extending a multi-module Python library for scientific computation (e.
    0 installs
56. ▌
    Methylation Region Genomic Context Assignment · holobiomicslab

    Use when after identifying differentially methylated bases or regions (via calculateDiffMeth() and getMethylDiff()), when you need to characterize WHERE these methylation changes occur relative to gene structure and CpG density landscapes.
    2 installs
57. ▌
    Sample Similarity Assessment From Methylation · holobiomicslab

    Use when after merging methylation calls across all samples using unite() to create a methylBase object, apply this skill to characterize whether replicate samples cluster together and to visualize methylation-driven separation between biological groups (e.g., test vs. control).
    2 installs
58. ▌
    Single Cell Atac Seq Dimensionality Reduction · holobiomicslab

    Use when after loading and preprocessing raw scATAC-seq data into an ArchR project object when you need to compute low-dimensional embeddings for clustering, UMAP/tSNE visualization, or integrated multi-omic analysis.
    2 installs
59. ▌
    Chemical Structure Representation Conversion · holobiomicslab

    Use when when you have .msp mass spectrometry metadata containing chemical identifiers (e.g., compound names or SMILES strings) and need to compute derived chemical properties (e.g., InChI, InChIKey, molecular formula) locally without network latency or service availability constraints.
    0 installs
60. ▌
    Community Metabolic Reconstruction Synthesis · holobiomicslab

    Use when you have draft metabolic reconstructions (in SBML or equivalent format) for multiple organisms sampled from a single ecological community (e.
    2 installs
61. ▌
    Conditional Dispatch Workflow Implementation · holobiomicslab

    Use when when you have loaded a raw mass spectrum (e.g., ESI_NEG_SRFA.d in Bruker or .raw format) and need to apply one of several noise-threshold strategies based on user preference or spectrum metadata.
    0 installs
62. ▌
    Converter Pipeline Integration And Execution · holobiomicslab

    Use when when you have a .msp mass spectra file with incomplete or missing chemical metadata fields (SMILES, InChI, CAS number, formula, InChIKey, IUPAC name) and need to populate those fields by querying multiple external chemical identifier services and local cheminformatics tools in parallel.
    0 installs
63. ▌
    Intensity Dependent Missing Value Simulation · holobiomicslab

    Use when augmenting mass spectrometry ion images in ISO mode (isotope ions from the same molecule) and you need to simulate intensity-dependent data loss that reflects real detector behavior where lower-intensity pixels are more likely to be missed or undetected.
    0 installs
64. ▌
    Internal Standardization With Isotope Labels · holobiomicslab

    Use when your IM-MS lipidomics samples have been spiked with fully labeled isotopic internal standards (e.
    2 installs
65. ▌
    JSON Serialization And Data Structure Design · holobiomicslab

    Use when you have inferred or discovered structured results (e.g., LDA-derived motif sets with mass compositions, neutral-loss patterns, and ranked database matches) that must be shared between tools, stored durably, or consumed by visualization or annotation pipelines.
    0 installs
66. ▌
    Mass Spectrometry Molecular Formula Handling · holobiomicslab

    Use when you have raw or processed FT-ICR MS spectra with detected peaks (m/z values) and need to: (1) assign elemental compositions to each peak, (2) filter assignments by mass error tolerance and isotopic presence, or (3) prepare a peak table with molecular formula annotations for chemodiversity.
    0 installs
67. ▌
    Molecular Fingerprint Bit Frequency Analysis · holobiomicslab

    Use when you have loaded a collection of molecular fingerprint vectors (e.g., from biosynfoni fingerprints deposited in Zenodo) and need to assess their statistical properties before using them for classification, similarity search, or method validation.
    0 installs
68. ▌
    Neural Network Layer Metadata Interpretation · holobiomicslab

    Use when after deploying a TensorFlow-backed classification service, you need to verify that the model's input layer names ('input_2048' and 'input_4096') and output layer name ('output') are correctly configured before constructing inference requests.
    0 installs
69. ▌
    Olden Method Feature Attribution Calculation · holobiomicslab

    Use when after training multiple MLPNN models (via cross-validation) on paired microbiome and metabolome data when you need to extract interpretable feature importance scores from network weights to identify which microbes drive metabolite predictions and group them into co-functional modules.
    0 installs
70. ▌
    Python Environment Setup And Reproducibility · holobiomicslab

    Use when when you need to execute a multi-backend visualization library (e.g., pyOpenMS-Viz with matplotlib, Bokeh, and Plotly) and must measure or validate execution times, memory usage, and output consistency across runs or team members.
    0 installs
71. ▌
    Pytorch Model Instantiation And Forward Pass · holobiomicslab

    Use when after defining a transformer encoder architecture with multi-head self-attention and positional encoding, and before training or inference on mass spectrometry data.
    0 installs
72. ▌
    Random Access Seekable File Interface Design · holobiomicslab

    Use when you have a large mzML file or text corpus (e.g., Moby Dick, proteomics run) stored in compressed or database format and need to retrieve specific spectra or chapters by ID without sequential iteration or full decompression.
    0 installs
73. ▌
    Regression Metric Computation And Comparison · holobiomicslab

    Use when you have trained two or more regression models (e.g., original vs. alternative GNN architectures) on the same training set and need to evaluate which generalizes better on held-out test data.
    0 installs
74. ▌
    Sqlite Query Execution And Cursor Management · holobiomicslab

    Use when you have mass spectrometry data stored in a SQLite database indexed by spectrum ID and need to retrieve specific spectra by ID (random access via __getitem__) or iterate through all spectra sequentially (via read method).
    0 installs
75. ▌
    Statistical Summary Computation Median Range · holobiomicslab

    Use when when you have a table of execution times or performance metrics indexed by two or more categorical dimensions (e.g., plot_type × backend, or sample × condition), and you need to compare central tendency and spread across groups to rank or benchmark alternatives.
    0 installs
76. ▌
    Strain Correlation Hypergeometric Adjustment · holobiomicslab

    Use when you have genomic clusters (GCFs) and metabolomic features (MFs) from paired microbial datasets, each with strain membership information, and you need to score potential links between them.
    0 installs
77. ▌
    Transformation Classification Biotic Abiotic · holobiomicslab

    Use when after mass-difference network generation has matched pairwise peak mass differences to a reference biochemical transformation key with mass error ≤1 ppm, and you need to distinguish metabolic transformations driven by microbial activity from those arising from non-biological chemical.
    0 installs
78. ▌
    XML Element Parsing And Object Serialization · holobiomicslab

    Use when you have spectrum or chromatogram data stored as XML strings (e.g., in a SQLite database indexed by spectrum ID) and need to access individual spectra by ID or iterate through them sequentially while working with a library like pymzML that expects Spectrum or Chromatogram objects.
    2 installs
79. ▌
    Automated Executable Distribution Generation · holobiomicslab

    Use when you need to produce final distributable executable artifacts for a Qt5-based C++ application across multiple platforms (macOS, Windows, Linux), and you want to avoid manual build–package–release steps.
    0 installs
80. ▌
    Baseline Model Implementation For Comparison · holobiomicslab

    Use when you are introducing a novel spectrum prediction model and need to demonstrate that performance improvements come from architectural innovation rather than experimental advantage.
    0 installs
81. ▌
    Batch Structure Inspection Macroscopic Scale · holobiomicslab

    Use when after loading log-transformed, pre-processed metabolomics feature abundance tables (samples × features, with batch identifiers in the first column) and prior to selecting a batch-effect correction model.
    0 installs
82. ▌
    Biomolecule Filtering By Abundance Threshold · holobiomicslab

    Use when after data transformation (e.g., log2 normalization) but before statistical analysis, when you have an expression matrix with missing values or high variance across samples and you need to remove unreliable biomolecules.
    0 installs
83. ▌
    Chemical Structure Web Service Communication · holobiomicslab

    Use when you have a collection of chemical compounds (identified by name, SMILES, InChI, or other standard identifier) that you need to classify by structural features, and you want to submit them in batch to a remote web service rather than performing local computation.
    0 installs
84. ▌
    Spectral Intensity Normalization Across Modalities · holobiomicslab

    Use when you have raw spectral data from multiple complementary spectroscopic techniques (NMR, HSQC, COSY, IR) that must be combined into joint training records for a multimodal deep learning model, and the raw intensity values or chemical shift ranges differ significantly between modalities due to.
    0 installs
85. ▌
    Chromatin Accessibility Footprint Visualization · holobiomicslab

    Use when use this skill after performing Tn5 bias correction and footprint scoring on ATAC-seq BAM files when you need to inspect the spatial distribution of Tn5 insertions around transcription factor binding sites, validate footprinting quality, or communicate differential TF occupancy patterns.
    1 install
86. ▌
    System Path Configuration And Environment Setup · holobiomicslab

    Use when you are setting up HiC-Pro or a similar multi-tool pipeline for the first time, or you need to validate that all required dependencies are installed and discoverable.
    2 installs
87. ▌
    Chemical Structure Sanitization And Validation · holobiomicslab

    Use when you have translated or raw SMILES strings from a chemical structure curation pipeline and need to remove invalid chemical structures, resolve sanitization errors (e.
    0 installs
88. ▌
    Class Stratified Calibration Model Application · holobiomicslab

    Use when you have a feature table with assigned biomolecular class labels (e.g., from preceding class assignment step) and raw ion mobility arrival time measurements from TWIM-MS data, and you need to compute class-appropriate CCS values for downstream multi-omic analysis.
    2 installs
89. ▌
    Container Volume Mounting And File Persistence · holobiomicslab

    Use when executing containerized conversion tools (e.g., AirdPro CLI) that must read vendor-format mass spectrometry raw files from the host filesystem and write converted output (e.g., .aird files) back to a persistent host directory. This is essential when first-run Wine initialization and .
    0 installs
90. ▌
    Ion Mobility Mass Spectrometry Data Processing · holobiomicslab

    Use when you have (LC-)IM-MS lipidomics data from samples spiked with U13C labeled internal standards (e.g., fully labeled yeast extract) and need to quantify and correct systematic CCS bias before downstream lipid identification or quantification.
    2 installs
91. ▌
    Metabolomics Quality Control Report Generation · holobiomicslab

    Use when after completing outlier detection, batch correction, and quality metric calculation on a SummarizedExperiment object using mzQuality's doAnalysis function, and after manually or automatically filtering compounds and samples using the 'use' column in rowData and colData.
    0 installs
92. ▌
    Molecular Weight Prediction With Modifications · holobiomicslab

    Use when when you have metabolite structures (as SMILES strings) and need to predict their observable m/z ions under non-standard ionization conditions imposed by a derivatizing matrix reagent (such as FMP-10).
    2 installs
93. ▌
    Representation Vector Dimensionality Reduction · holobiomicslab

    Use when after obtaining 512-dimensional representation vectors from the Encoder module, when you need to compress these vectors for visualization, clustering, or downstream classification tasks on mass spectrometry imaging data while maintaining interpretability of ion relationships.
    0 installs
94. ▌
    Abundance Normalization And Summary Statistics · holobiomicslab

    Use when after peaks have been assigned to heteroatom classes (e.g., CHO, CHON, CHOS, CHOP) and you need to compare molecular composition across samples, classes, or time series.
    2 installs
95. ▌
    Biweight Midcorrelation Similarity Computation · holobiomicslab

    Use when you have normalized and imputed metabolite abundance measurements (as a MultiAssayExperiment object or similar matrix) and need to construct a correlation network for co-expression module discovery. Use it specifically when outlier-robust similarity is required—i.
    0 installs
96. ▌
    Checkpoint Serialization And Model Persistence · holobiomicslab

    Use when after completing a full training loop on preprocessed molecular graph data and validating model performance on a held-out validation set.
    0 installs
97. ▌
    Circular Dependency Avoidance In Method Design · holobiomicslab

    Use when you are implementing multiple accessor methods on a backend class that logically depend on each other (e.g., one returns full data and another returns column metadata), and both methods are required by downstream code.
    0 installs
98. ▌
    Coding Potential Prediction And Classification · holobiomicslab

    Use when you have differentially expressed isoform or exon FASTA sequences from transcript assembly or isoform-level analysis (e.g., IsoformSwitchAnalyzer output) and need to distinguish functional protein-coding transcripts from non-coding RNA.
    0 installs
99. ▌
    Command Line Software Installation From Github · holobiomicslab

    Use when you need to install a Python package that is distributed via GitHub but not yet (or only occasionally) published to PyPI, such as pyBaf2Sql for Bruker .baf/.d mass spectrometry imaging data conversion.
    0 installs
100. ▌
     Comparative Statistical Testing Across Methods · holobiomicslab

     Use when when you have applied multiple pathway analysis methods to the same metabolomics peak intensity dataset and need to determine which method produces more stable pathway activity scores under realistic perturbation conditions (noise and missing peaks).
     0 installs