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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Neural Network Transfer Learning For Spectral Models · holobiomicslab

   Use when your input is a corpus of MS/MS spectra with annotated molecular formulas and adduct types that represent a new ionisation mode, instrument type, or adduct chemistry not well-represented in the pre-trained model's training data. You have access to a trained formula transformer (e.
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   One Hot Encoding Categorical Chromatography Features · holobiomicslab

   Use when you have raw HPLC column metadata containing categorical fields (e.g., column manufacturer 'Waters', USP type 'L1', solvent identities 'H2O'/'MeOH'/'ACN') that must be converted into numerical representations before featurization for a machine learning pipeline.
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   Precision Recall Curve Generation And Interpretation · holobiomicslab

   Use when you have computed spectral similarity scores from multiple methods (e.g., MS2DeepScore, Spec2Vec, modified cosine) on the same set of spectrum pairs, have assigned ground-truth structural similarity labels (e.
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4. ▌
   Precision Recall Optimization In Spectral Annotation · holobiomicslab

   Use when you have extracted fragmentation patterns from a collection of MS/MS spectra (using mineMS2) and have partitioned spectra into components via GNPS molecular networking (e.g., connected components, cliques, or high-similarity pairs with cosine > threshold).
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5. ▌
   Spectral Feature Clustering By Intensity Correlation · holobiomicslab

   Use when you have an annotated LC-MS feature table with KEGG candidate matches and adduct assignments (output from the matching stage), and you need to disambiguate which features co-elute and correlate in intensity, signaling a common metabolite origin before applying adduct-based filtering.
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6. ▌
   Statistical Significance Testing P Value Calculation · holobiomicslab

   Use when after standardizing link scores (strain correlation and IOKR) across all potential GCF-MF pairs in a metabologenomics dataset, perform significance testing to determine whether validated links show statistically distinguishable score distributions from the background.
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7. ▌
   Tandem Mass Spectra Structural Similarity Assessment · holobiomicslab

   Use when you have pairs of cleaned tandem mass spectra with known chemical structure annotations (InChIKey, SMILES, or InChI), and you need to predict Tanimoto structural similarity scores directly from spectral data without pre-computing molecular fingerprints.
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8. ▌
   Tandem Mass Spectrum Preprocessing And Normalization · holobiomicslab

   Use when you have acquired raw MS/MS spectra (in MGF or mzML format) from a mass spectrometry instrument or public repository (e.g., MassIVE, MetaboLights, GNPS) that will be used for de novo chemical formula ranking or adduct assignment.
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9. ▌
   Targeted Metabolite Detection Parameter Optimization · holobiomicslab

   Use when when you have centroided .mzML LC–MS runs and a target list (compound ID, theoretical m/z, expected RT, polarity) but are uncertain whether your m/z and RT windows are wide enough to capture all targets without false positives.
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10. ▌
    Molecular Geometry Neural Network Potential Evaluation · holobiomicslab

    Use when after RDKit has generated multiple conformations for a molecule in an SDF or XYZ format, and you need to reduce the conformational ensemble to a tractable size (by energy-based ranking) before submitting to expensive quantum-chemical calculations (e.g., QUICK).
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11. ▌
    Biosynthetic Gene Cluster Detection And Annotation · holobiomicslab

    Use when you have assembled microbial genomes (nucleotide FASTA files) and want to identify biosynthetic potential and group related BGCs for downstream linking with metabolomic data;
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12. ▌
    CLI Application Invocation With File Io Management · holobiomicslab

    Use when when you have vendor mass spectrometry raw files (e.g., .raw format) that must be converted to an open format (Aird) using a Windows .
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13. ▌
    Mass Spectrometry Visualization Backend Comparison · holobiomicslab

    Use when you have a mass spectrometry visualization library that claims to support multiple plotting backends and need to verify that: (1) all backends produce functionally equivalent outputs, (2) execution times are consistent with reported benchmarks, and (3) the library scales appropriately.
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14. ▌
    Molecular Property Prediction Feature Construction · holobiomicslab

    Use when when you have molecular structures (SMILES or graph formats) and need to predict a physicochemical or spectral property (e.g., infrared spectra) using a graph neural network architecture. Use this skill when the base model architecture (e.
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15. ▌
    Over Representation Analysis Pvalue Interpretation · holobiomicslab

    Use when when you have run ORA on a metabolomics dataset and obtained p-values for pathway enrichment, but you need to assess whether observed significance is genuine or an artifact of incomplete metabolite coverage.
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16. ▌
    Retention Time Abundance Correlation Visualization · holobiomicslab

    Use when after applying AbundanceSimilarityParam (with threshold ≥0.7 and log2 transform) to retention-time-based feature groups from SimilarRtimeParam, when you need to examine the internal correlation structure of specific feature sub-groups (e.g., FG.
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17. ▌
    Structure Organism Pair Counting And Deduplication · holobiomicslab

    Use when when you have downloaded a curated structure-organism dataset (such as LOTUS) in TSV or CSV format with separate 2D and 3D structure-organism pair tables, and need to produce authoritative headline counts of unique referenced pairs, unique curated structures, unique organisms, and source.
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18. ▌
    Approximate Nearest Neighbor Indexing Construction · holobiomicslab

    Use when when you have a large spectral library (hundreds of thousands to millions of spectra) and need to perform open modification searching on query spectra where exhaustive comparison against all library entries is computationally prohibitive.
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19. ▌
    Coefficient Of Variation Calculation And Filtering · holobiomicslab

    Use when after loading and applying minimum non-missing-value thresholds to an omics expression dataset (proteomics, metabolomics, or other panomics data).
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20. ▌
    Correlation Coefficient Computation Across Samples · holobiomicslab

    Use when after XCMS feature detection and retention time correction, when you need to group features derived from the same compound. Features from the same compound show correlated quantitative trends across samples;
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21. ▌
    Data Quality Assessment From Molecular Descriptors · holobiomicslab

    Use when processing spectral datasets from open mass spectra libraries (OMSLs) where structural identifiers and ionization metadata are incomplete or inconsistent.
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22. ▌
    Dimensionality Reduction And Clustering Evaluation · holobiomicslab

    Use when you have high-dimensional feasible flux distributions sampled from constraint-based metabolic models for multiple biological samples (e.
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23. ▌
    Flux Distribution Interpretation Across Cell Lines · holobiomicslab

    Use when you have sampled 10,000+ steady-state flux solutions for each of multiple cell lines from a constraint-based model; computed Reaction Propensity Scores (RPS) from substrate abundance (metabolomics) and Reaction Activity Scores (RAS) from gene expression (transcriptomics);
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24. ▌
    Gzip Compression With Random Access Implementation · holobiomicslab

    Use when you have a large text or structured file (mzML, XML, plain text) that you want to compress while retaining the ability to retrieve specific logical blocks (chapters, spectra, records) by identifier without decompressing the entire file.
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25. ▌
    Hierarchical Clustering Euclidean Complete Linkage · holobiomicslab

    Use when you have a normalized microbe-metabolite feature attribution score matrix (rows = microbes, columns = metabolites) and need to explore hierarchical structure and visually assess similarity patterns before determining the optimal number of clusters via consensus clustering.
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26. ▌
    Hypergeometric Distribution Null Model Application · holobiomicslab

    Use when when you have raw strain correlation scores computed across multiple GCF–MF link pairs from a metabologenomics dataset and need to compare score magnitudes across different links.
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27. ▌
    Message Passing Neural Network Architecture Design · holobiomicslab

    Use when when you have a working base MPNN implementation (e.g., chemprop) and need to adapt it for a new molecular property target (e.g., spectral data) that requires custom input processing, intermediate feature representations, or output layer modifications beyond the original model's scope.
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28. ▌
    Multi Modal Spot Validation And Quality Assessment · holobiomicslab

    Use when after performing spot_align_byknn to map SM spots to ST spots, validate that all SM spots have been successfully assigned and that the Euclidean distance distributions between SM spots and their assigned nearest ST neighbors are reasonable (no outliers or failed assignments that would.
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29. ▌
    Multiple Testing Correction And P Value Adjustment · holobiomicslab

    Use when when you have generated raw p-values from differential expression analysis on preprocessed count matrices (mRNA, miRNA, isoforms, lipids, or proteins) using edgeR, DESeq2, or RankProduct and need to identify statistically significant features while controlling familywise error rate or.
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30. ▌
    Organism Context Metabolic Plausibility Assessment · holobiomicslab

    Use when when BioTransformer or another metabolism predictor has generated a list of candidate metabolite structures (in SMILES or InChI format) for a query compound, and you need to identify which candidates are most likely to occur in a specific organism or environment (e.
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31. ▌
    Peak Parameter Optimization For Targeted Compounds · holobiomicslab

    Use when you have centroided high-resolution Orbitrap or GC-CI-MS mzML files and a formulaTable of target compounds with known m/z, retention time, and molecular formula, and you need to extract isotopologue abundances and quantification metrics (area, maxo intensity, ppm error) for each labeled.
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32. ▌
    Plant Species Authentication Via Mass Spectrometry · holobiomicslab

    Use when when you have mass spectrometry raw data (DI-MS or ASAP-MS format) from plant samples that are easily confused due to morphological similarity, or when you need to verify or authenticate the species identity of a plant material against a reference database.
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33. ▌
    Redundancy Filtering In Biosynthetic Gene Clusters · holobiomicslab

    Use when when you have a collection of tokenised BGCs (represented as combinations of Pfam domains and subPfams) that may contain redundant or near-identical sequences, and you need to reduce computational burden and avoid biased sub-cluster detection caused by over-representation of similar BGCs.
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34. ▌
    Singularity Container Image Building And Execution · holobiomicslab

    Use when you have a Docker image published to a registry (e.g., docker://stravsm/msnovelist6), need to run it on an HPC cluster with SLURM scheduling, and must allocate specific hardware resources (GPUs, RAM) per job.
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35. ▌
    Sphinx Gallery Execution And Performance Profiling · holobiomicslab

    Use when you have a Sphinx-based documentation project with multiple gallery scripts (e.
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36. ▌
    Validation Test Design For Biochemical Identifiers · holobiomicslab

    Use when you have implemented or integrated a biochemical identifier converter (e.
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37. ▌
    Weighted Correlation Network Module Interpretation · holobiomicslab

    Use when after WGCNA has identified and named metabolic correlation modules from preprocessed, normalized, and imputed metabolomic data, and you need to test whether specific modules show statistically significant association with a known sample grouping (e.
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38. ▌
    Z Score Normalization For Cross Dataset Comparison · holobiomicslab

    Use when you have multiple scoring functions (e.g., strain correlation or spectral similarity scores) computed over heterogeneous GCF-MF or BGC-spectrum link sets where raw scores cannot be directly compared due to differences in set sizes (GCF size g, MF size m, overlap o) or null-model.
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39. ▌
    Nearest Neighbor Graph Construction Pynndescent · holobiomicslab

    Use when when analyzing spatial molecular data (e.g., from tissue sections or microscopy) where you need to build k-nearest neighbor graphs on high-dimensional coordinate arrays (n_obs × n_dims) and exact nearest neighbor computation is too slow or memory-intensive;
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40. ▌
    Reduction Plot Interpretation And Visualization · holobiomicslab

    Use when after computing gene set enrichment scores (e.g., via GESECA on reverse PCA feature loadings) on a single-cell or bulk dataset with an existing dimensionality reduction (tSNE, UMAP, PCA).
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41. ▌
    Statistical Precision Comparison Ranked Outputs · holobiomicslab

    Use when when a statistical method offers a parameter to trade computational cost for precision (e.
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42. ▌
    Unified Mobility Scale Construction Across Polarities · holobiomicslab

    Use when you have CE-MS raw data in OnDiskMSnExp format with both positive and negative polarity acquisitions, migration times that vary due to electroosmotic flow drift, and access to two well-characterized mobility markers (e.g., Paracetamol and Procaine with known charges and migration times).
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43. ▌
    Automated Peak Detection Without Conventional Picking · holobiomicslab

    Use when you have a two-dimensional GC–MS or LC–MS dataset (m/z vs retention time) and need to identify discriminative analyte features without relying on conventional peak picking algorithms. This is especially valuable when analyzing complex, low-abundance samples (e.
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44. ▌
    Comparative Algorithm Benchmarking For Peak Detection · holobiomicslab

    Use when you have developed or adapted a peak detection method for chromatography–mass spectrometry and need to validate its reliability against an established baseline on the same raw GC–MS dataset. Specifically when: (1) the input is raw GC–MS data in m/z vs retention time format;
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45. ▌
    Ionization Mode Detection From Mass Spectrometry Data · holobiomicslab

    Use when when you have raw LC-MS data in mzML format (converted from .raw or acquired directly in that format) and need to invoke Asari for feature extraction, but the ionization mode is not explicitly specified in your experimental metadata or pipeline configuration.
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46. ▌
    Ppb Level Marker Detection And Sensitivity Assessment · holobiomicslab

    Use when you have raw GC–MS or LC–MS data in two-dimensional m/z vs retention time format and need to identify marker features at parts-per-billion sensitivity without relying on conventional peak picking.
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47. ▌
    Spectrum Document Conversion Peak Loss Representation · holobiomicslab

    Use when when preparing MS/MS spectral data for training word-embedding models (Word2Vec, Skip-gram, CBOW) that will learn relationships between fragment ions and neutral losses.
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48. ▌
    Deep Learning Model Inference And Ensemble Prediction · holobiomicslab

    Use when you have a trained deep learning model and want to quantify prediction uncertainty for each input pair or decision point. Use this when you need to identify low-confidence predictions (high IQR) and filter them out to reduce error in specific score ranges (e.
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49. ▌
    Machine Learning Model Training With Cross Validation · holobiomicslab

    Use when when you have a labeled peak quality matrix (with known pass/fail labels), need to objectively compare performance across multiple classification algorithms (e.
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50. ▌
    Mass Spectrometry Data Coordinate System Construction · holobiomicslab

    Use when when you have processed LC-MS/MS spectral data in .mgf format with precomputed ms2deepscore similarity matrices and need a 2-D overview representation that preserves local spectral relationships for interactive exploration and visualization.
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51. ▌
    Mass Spectrometry Deconvolution Algorithm Application · holobiomicslab

    Use when you have raw DDA, DIA (MS^E, AIF, SWATH-MS), or MS1-only mass spectrometry data in mzML, mzXML, or netCDF format and need to deconvolute fragmentation spectra by linking precursor ions to their fragment ions based on retention time and m/z relationships.
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52. ▌
    Metabolic Reaction Classification By Regulatory Layer · holobiomicslab

    Use when you have integrated transcriptomics, intracellular metabolomics, and extracellular flux ratio data from multiple cell lines or conditions, and need to determine whether observed differences in metabolic fluxes originate from gene expression changes, substrate availability changes, or both.
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53. ▌
    Metabolomics Data Integration With Metabolic Networks · holobiomicslab

    Use when you have measured intracellular metabolite concentrations (e.g., via LC–MS/MS) across multiple cell lines or samples and want to predict which metabolic reactions are substrate-limited versus transcriptionally regulated.
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54. ▌
    Metabolomics Feature Selection Significance Filtering · holobiomicslab

    Use when you have fitted an MB-PLS model on multi-assay LC-MS intensity data (e.g., HPOS, LPOS, LNEG), computed MB-VIP scores for all features, and need to identify which features are statistically significant for your phenotypic outcome.
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55. ▌
    Python Package Installation And Dependency Management · holobiomicslab

    Use when when setting up a new computational environment for tandem MS/MS spectrum clustering or other proteomics analysis, and you need to install a tool (like falcon) that depends on specific versions of auxiliary packages (like spectrum-utils==0.3.5).
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56. ▌
    Relative Standard Deviation Calculation Qc Replicates · holobiomicslab

    Use when you have a peak table from XCMS preprocessing with intensity measurements for the same set of metabolites across multiple QC replicate injections (samples marked SampleType='LQC'), and you need to filter out EICs with poor reproducibility before evaluating peak quality or training a.
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57. ▌
    Spectral Dataset Partitioning And Train Test Curation · holobiomicslab

    Use when when you have a pre-cleaned spectral library (e.g., GNPS, MoNA, or MTBLS1572) with an existing training/test boundary established by prior work (e.g., MSBERT), and you need to report model performance with uncertainty quantification across multiple random partitions.
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58. ▌
    Statistical Significance Estimation Mass Spectrometry · holobiomicslab

    Use when after aligning fragment ions between two tandem mass spectra (query and reference) using maximum weight matching and you need to assign confidence scores to the matched ion pairs.
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59. ▌
    Tandem Mass Spectrum Deconvolution Isotope Annotation · holobiomicslab

    Use when you have aligned features characterized across multiple dimensions (m/z, drift time, retention time) and need to: (1) resolve MS/MS spectra that may contain fragments from multiple co-eluting or co-mobilizing precursors; (2) identify and validate isotopic signatures (e.
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60. ▌
    Bioinformatics Tool Version Compatibility Assessment · holobiomicslab

    Use when before executing a complex bioinformatics pipeline (such as Hi-C data processing) that depends on multiple third-party tools with explicit version constraints.
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61. ▌
    CI CD Workflow Adaptation To Organization Standards · holobiomicslab

    Use when when a Python package is being relocated to a new GitHub organization (e.
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62. ▌
    Collision Cross Section Measurement Quality Control · holobiomicslab

    Use when you have IM-MS lipidomics data from samples spiked with U13C-labeled internal standards (fully labeled yeast extract) and you need to quantify whether measured CCS values deviate systematically from theoretical values, or when you want to correct CCS measurements before downstream lipid.
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63. ▌
    Principal Component Extraction From Pathway Subsets · holobiomicslab

    Use when you have a log2-normalized, zero-mean and unit-variance standardized intensity matrix of metabolite features (rows=metabolites, columns=samples) and need to compute a single activity score per pathway that reflects the coordinated expression behavior of all metabolites assigned to that.
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64. ▌
    Statistical Significance Testing Metabolic Networks · holobiomicslab

    Use when you have sampled flux distributions from two or more constraint-based metabolic models representing different biological conditions (e.
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65. ▌
    Structural Similarity Calculation Fingerprint Based · holobiomicslab

    Use when you have a set of compounds (e.g., novel NPS analogues in an evaluation dataset) and need to classify them as structurally similar to or divergent from a reference set (e.g., training compounds).
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66. ▌
    Antismash Bgc Directory Organization And Validation · holobiomicslab

    Use when when preparing genomic data for NPLinker analysis and you have AntiSMASH BGC predictions that need to be validated and organized into NPLinker's standardized directory layout.
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67. ▌
    Batch Effect Preprocessing With Replicate Structure · holobiomicslab

    Use when you have metabolomics data from multiple experimental batches (≥2) with embedded replicate samples (identical samples run at different points within or across batches), log-transformed raw assays containing ≥50% missing values per batch, and a need to harmonise metabolite quantification.
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68. ▌
    Bigscape Output Version Detection And Compatibility · holobiomicslab

    Use when when preparing NPLinker input data and the BigScape directory exists but its format is unknown or mixed (e.g., migrated workflows, third-party data, or legacy archives). Specifically: if local mode and BigScape directory is missing, generate it;
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69. ▌
    Comparative Output Analysis Across Parameter States · holobiomicslab

    Use when when you need to validate that a boolean control parameter in BioTransformerAPI (useCypReact) properly gates a filtering module, or when you want to understand the qualitative and quantitative impact of CypReact filtering rules on predicted metabolite outputs for a given substrate and.
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70. ▌
    Corrected Uncorrected Data Comparison Visualization · holobiomicslab

    Use when after preprocessing and log-transformation of metabolomics feature abundance matrices (samples as rows, metabolic features as columns), when you have multiple candidate batch-correction models (e.
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71. ▌
    Cross Batch Metabolite Quantification Harmonization · holobiomicslab

    Use when you have multiple SummarizedExperiment objects representing separate metabolomics assay batches with different metabolite coverage and missing-value patterns, and you need to identify a common metabolite set quantified across all batches before applying hierarchical batch normalization or.
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72. ▌
    Cross Validated Model Performance Evaluation 10fold · holobiomicslab

    Use when when you have trained a neural network or regression model to predict metabolite abundances from microbiome features and need to measure how well the model generalizes to unseen samples. Apply this skill when you want to compare multiple competing models (e.
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73. ▌
    Custom File Handler Class Design For Indexed Access · holobiomicslab

    Use when your input is a large mzML or text file that would benefit from compression without sacrificing random-access performance, and you need to retrieve specific logical blocks (e.g., a chapter, spectrum, or database record) by key without decompressing the entire file.
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74. ▌
    Deep Learning Architecture Design For Sequence Data · holobiomicslab

    Use when when you have raw co-fractionation/mass-spectrometry elution profiles (normalized intensity vectors across fractions) paired with labeled protein interaction ground truth, and you want to avoid hand-crafted features (e.
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75. ▌
    Docker Container Environment Variable Configuration · holobiomicslab

    Use when when deploying a Java application in a Docker container and you need to adjust JVM heap memory settings (maximum and initial heap size) without modifying the container image.
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76. ▌
    Feature Metadata Extraction From Clustering Objects · holobiomicslab

    Use when after RAMClustR clustering and do.findmain molecular weight inference have been completed on XCMS-detected metabolomics features.
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77. ▌
    Grid Search Evaluation And Threshold Identification · holobiomicslab

    Use when you have a fitted alignment model (e.g., metabCombiner object with pre-aligned feature pair candidates and RT spline mapping) and known shared compound identities (ground truth) from reference datasets, and you need to determine which combination of three or more continuous parameters (e.
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78. ▌
    Hierarchical Cluster Analysis Dendrogram Generation · holobiomicslab

    Use when you have a feature-by-sample matrix (finalData) of metabolomic intensities and sample group labels (finalLabel), and you want to visualize how samples cluster together based on their overall metabolomic similarity.
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79. ▌
    Hypergeometric Distribution Probability Calculation · holobiomicslab

    Use when when you have raw strain correlation scores computed across GCF–MF pairs of varying sizes (different numbers of strains in each set) and need to make those scores comparable.
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80. ▌
    In Memory Cache Implementation For Repeated Queries · holobiomicslab

    Use when when deploying a high-throughput molecular classification API (e.g., /classify endpoint) where the same SMILES strings are expected to be queried repeatedly across multiple users or time windows, and response latency is a performance constraint.
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81. ▌
    Maldi Imaging Mass Spectrometry Data Interpretation · holobiomicslab

    Use when you have paired pre- and post-MALDI microscopy images with visible, non-overlapping ablation marks, MALDI raw data files (.RAW, .UDP, .imzML, .ibd) analyzed by METASPACE, and a segmented cell mask from CellProfiler.
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82. ▌
    Metabolic Network Database Output And Serialization · holobiomicslab

    Use when after completing a Pickaxe reaction network expansion across N generations, when you need to store the predicted compounds and reactions in a format suitable for querying, sharing, or integration with other bioinformatic pipelines.
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83. ▌
    Metabolite Composition Comparison Across Treatments · holobiomicslab

    Use when you have normalized peak intensity tables from FT-ICR MS data (e.g., MetaboDirect .
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84. ▌
    Metabolomic Dataset Preprocessing And Normalization · holobiomicslab

    Use when you have raw or minimally processed FT-ICR MS peak tables in Formularity .
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85. ▌
    Metabolomic Feature Filtering Threshold Application · holobiomicslab

    Use when after running the Marr() function on preprocessed metabolomic data (with missing value imputation and normalization already complete) when you need to distinguish reproducible from non-reproducible features and sample pairs.
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86. ▌
    Molecular Structure Canonicalization And Validation · holobiomicslab

    Use when immediately after generating candidate transformation products from biotransformation rules.
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87. ▌
    Multi Mode Filter Application High Dimensional Data · holobiomicslab

    Use when you have high-dimensional biological data (e.
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88. ▌
    Multiprocessing Process Spawning And Pid Management · holobiomicslab

    Use when when deploying a Streamlit workflow app in offline mode (online_deployment: false) or when Redis is unavailable in online mode, and you need to launch workflows as independent background processes while maintaining the ability to track, recover, or cancel them later by their PID.
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89. ▌
    Omics Data Quality Assessment Normalization Context · holobiomicslab

    Use when after loading peptide or protein-level quantification matrices with sample metadata into pmartR, and before proceeding to statistical analysis (ANOVA, G-test).
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90. ▌
    P Value Computation And Multiple Testing Correction · holobiomicslab

    Use when after matched lipid abundances have been grouped by experimental condition and descriptive statistics (mean, SD, median) calculated per group.
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91. ▌
    Pc Selection Via Acceleration And Parallel Analysis · holobiomicslab

    Use when when preparing metabolomic or multivariate count data for outlier detection in PC space, or when you need to reduce dimensionality while retaining only statistically significant components.
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92. ▌
    Principal Component Analysis Multivariate Reduction · holobiomicslab

    Use when after normalizing and log-transforming lipidomics abundance data (e.
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93. ▌
    Pymzml Reader Initialization With Custom Parameters · holobiomicslab

    Use when you have an mzML file (e.g. Manuels_customs_ids.mzML) with non-standard custom index identifiers that cannot be parsed by pymzML's default index parser.
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94. ▌
    Quality Control Sample Integration In Normalization · holobiomicslab

    Use when your multi-class metabolomic peak table includes quality control samples (technical replicates) but no internal standards, and you need to compare the performance of multiple preprocessing workflows (normalization, imputation, transformation methods) to select the optimal pipeline for.
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95. ▌
    Semantic Role Assignment For Mass Spectrometry Data · holobiomicslab

    Use when you have uploaded a delimited data file (comma-, semicolon-, or tab-separated) with a header row into Punc'data and need to ensure that each column is correctly mapped to its semantic role (m/z, intensity, formula, or other mass spectrometry attributes) before proceeding to analysis.
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96. ▌
    Summarized Experiment Initialization And Population · holobiomicslab

    Use when when beginning a metabolomics analysis workflow in maplet, you have raw or preprocessed metabolomics data (assay measurements) and associated sample metadata (colData) or feature annotations (rowData), and you need to create a single, unified container that will hold data, intermediate.
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97. ▌
    Taxonomic Nomenclature Normalization And Validation · holobiomicslab

    Use when you have organism names originating from 31+ heterogeneous natural product databases that use different taxonomic authorities, nomenclature versions, or rank assignments, and you need to harmonize them into a single organism subgraph with validated ranks before linking to chemical.
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98. ▌
    Microarray Expression Normalization Log Quantile · holobiomicslab

    Use when when you have raw or minimally processed microarray expression data (e.g., from GEO) with intensity values that exhibit sample-to-sample distributional differences and variance heterogeneity.
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99. ▌
    Spatial Coordinate Integration With Imaging Data · holobiomicslab

    Use when you have a spatial omics dataset (AnnData object with coordinate columns like 'x', 'y', 'z') and an associated tissue image file (e.g., TIFF, PNG, or HE-stained histology), and you need to extract image-based morphological features (e.
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100. ▌
     Consensus Spectrum Assembly From Fragmentation Spectra · holobiomicslab

     Use when you have detected a single chromatographic peak in DDA LC-MS/MS data that generated multiple MS2 fragmentation spectra (e.
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