Productivity

holobiomicslab Skill

Use when when you have a SummarizedExperiment containing metabolomic abundances and a corresponding vector of quality metrics (e.g., coefficient of variation computed across QC samples), and you need to filter to retain only features meeting a reproducibility threshold (e.g., CV ≤ 0.

holobiomicslab Skill

Use when you need to support multiple plotting backends for the same data visualization task, and you want to centralize backend selection logic so that users can specify their preferred rendering engine (matplotlib, bokeh, or plotly) at call time without modifying the core plotting logic.

holobiomicslab Skill

Use when investigating how a specific pull request (e.g., PR #72 introducing MS2Query's two-branch workflow split) modified the codebase architecture, control flow, or data routing.

holobiomicslab Skill

Use when you have a versioned workflow definition file (YAML or JSON) from a specific release commit and need to verify it conforms to the project's schema specification, validate the presence of all required metadata fields (name, version, inputs, outputs, steps), and detect syntax errors or.

holobiomicslab Skill

Use when you have a collection of antiSMASH-processed GenBank files (or custom BGC GenBank files prepared via the provided converter script) organized in a structured input folder, and you want to cluster them into Gene Cluster Families (GCFs) to chart biosynthetic diversity or identify.

holobiomicslab Skill

Use when when you have received a GitHub repository URL for a computational workflow (e.g., ENPKG full workflow) and need to prepare your local machine to execute the workflow.

holobiomicslab Skill

Use when before installing ENPKG dependencies for the first time, or when setting up the workflow on a new machine or user account. Trigger when you have cloned enpkg_full or enpkg_workflow and need to install runtime and optional development dependencies in isolation.

holobiomicslab Bundle

Use when you want chemical-class-level annotations for untargeted LC-MS/MS features rather than exact structures — determine molecular formulas with SIRIUS, compute CSI:FingerID fingerprints, and predict compound classes with CANOPUS and NPClassifier (superclass / class / pathway), producing a class-annotated feature table for chemical-inventory and enrichment analysis.

holobiomicslab Skill

Use when when you have pre-computed dense embeddings for query spectra (unknown compounds) and reference spectra (spectral library), and you need to rank library entries by similarity to each query for compound identification or structural similarity retrieval.

holobiomicslab Skill

Use when after running Enrichment() on a configured EnrichParam object (via KEGG_Enrich_PlotPanel or similar), when you have a full enrichment result table and need to reduce it to pathway hits meeting a specific significance threshold before visualization or export.

holobiomicslab Skill

Use when you have generated a lipid spectral library (with lipid identities, adducts, m/z values, and fragmentation patterns) and need to export it for downstream mass spectrometry analysis on either an Orbitrap (via Excalibur DDA) or via Skyline's transition-based workflow.

holobiomicslab Skill

Use when after invoking the DEIMoS CLI with a configuration file and allowing the Snakemake workflow to execute, use this skill to confirm successful completion of all workflow rules.

holobiomicslab Skill

Use when you are designing a new backend or data container that must integrate seamlessly with an existing Spectra-based workflow. You have identified a virtual parent class (e.

holobiomicslab Skill

Use when you have a set of lipid targets defined by species name, acyl chain composition, and expected adducts, and you need to configure a targeted mass spectrometry workflow (PRM or MRM) in Skyline.

holobiomicslab Skill

Use when after implementing or deploying a containerized Nextflow workflow that processes LC-HRMS metabolomics .

holobiomicslab Skill

Use when when processing open mass spectrometry library (OMSL) data that may contain duplicate spectral records (e.

holobiomicslab Skill

Use when after completing a hierarchical batch normalisation workflow (e.g., hRUV with intra-batch loess smoothing and inter-batch RUV-III correction) to verify that normalisation has eliminated run-order signal drift and batch-specific effects visible in raw or imputed assays.

holobiomicslab Skill

Use when implementing online task queue deployments (RQ + Redis) where job execution may outlive the originating web session, or where workers may restart unexpectedly.

holobiomicslab Skill

Use when you have raw unnormalized metabolomics intensity data organized by batch and sample type (QC vs. biological), and you need to remove systematic variation (drift, batch effects) while preserving biological signal.

holobiomicslab Skill

Use when after completing dereplication and cosine similarity clustering in the MolNotator workflow, when you have merged, dereplicated molecular and ion data (output from mode_merger and dereplicator steps) and need to assemble the final molecular network representation connecting predicted.

holobiomicslab Skill

Use when when you have raw LC-MS/MS spectral data in .

holobiomicslab Skill

Use when when you have run a spectral networking job on GNPS (e.g. ProteoSAFe-METABOLOMICS-SNETS-V2) and need to reuse the network output files locally with MetaMiner or another tool that accepts spectral network input directories.

holobiomicslab Skill

Use when after automated peak detection has identified candidate peaks from LC-MS mzML files, but before exporting the final metabolite library. Use this skill when you need to: (1) optimize noise and peak-detection parameters by visualizing their effect on a representative subset of peaks;

holobiomicslab Skill

Use when you have created a GNPS molecular network (classical or feature-based workflow) and run an MS2LDA experiment on the corresponding MGF spectra, and you want to annotate network nodes with shared Mass2Motifs and chemical class information to interpret the structural basis of network.

holobiomicslab Skill

Use when when beginning a MEMO analysis workflow with raw or unaligned MS2 spectra files and needing to extract fragmentation data and precursor information before counting MS2 peaks and neutral losses to generate sample fingerprints.

holobiomicslab Skill

Use when you have DDA (data-dependent acquisition) LC-MS/MS data with MS2 spectra and want to discover metabolic features that may be missed by MS1-only peak picking, or when you need an alternative feature extraction workflow that leverages fragmentation patterns to identify true metabolite.

holobiomicslab Skill

Use when when you have a pre-trained encoder (e.g., TCN spectrum encoder in FIDDLE) that has learned useful representations on a source task (e.g., MS/MS spectrum encoding), and you want to train lightweight task-specific modules (e.

holobiomicslab Skill

Use when you have downloaded a Jupyter notebook from a published metabolomics workflow repository (e.

holobiomicslab Skill

Use when when a spectral matching tool produces mixed output containing both exact library matches and analog search results, and your analysis or publication requires separate handling, interpretation, or reporting of these two match classes.

holobiomicslab Skill

Use when when you have aligned ChIP-Seq reads (single-end BED or paired-end BEDPE format) and need to identify enriched genomic regions by comparing ChIP signal against control background, with the ability to customize fragment length estimation, local bias calculation, and peak score thresholds.

holobiomicslab Skill

Use when when beginning a new mass spectrometry analysis workflow with raw spectral data files in mzML, mzXML, msp, MGF, or JSON format.

holobiomicslab Skill

Use when when integrating MSMetaEnhancer into Galaxy or another workflow platform and you need to dynamically populate conversion option menus without hardcoding service-specific logic.

holobiomicslab Bundle

Use when you have untargeted HRMS data and want to screen for a defined suspect list of environmental / exposure-relevant compounds — detect features, match them to suspect-list entries by exact mass/RT/MS2, elucidate structures of hits by in-silico fragmentation, and assign identification confidence levels (Schymanski), producing a confidence-annotated suspect-hit table.

holobiomicslab Bundle

Use when you have targeted LC-MS data for a defined panel of analytes and want absolute or relative concentrations — extract and integrate the target transitions/ion chromatograms, build calibration curves from standards with internal-standard normalization, apply them to samples, and QC the batch (response drift, QC-sample RSD) to a reportable quantification table.

holobiomicslab Skill

Use when when beginning an untargeted LC-MS annotation workflow, before attempting to match experimental m/z peaks to metabolite identities.

holobiomicslab Skill

Use when when you have MS/MS spectra from both query compounds and a reference library and need to decide which similarity metric will maximize identification accuracy (true positive rank, precision@k) or when benchmarking a new compound identification workflow against a known-good reference.