Claude Skills by HolobiomicsLab

Use when you have raw LC-MS metabolomics data from multiple disease groups

Use when you have (1) metabolite-disease correlation matrices and protein

Use when when evaluating a taxonomy classification model on held-out

Use when you have completed LC–MS/MS feature detection and annotation

Use when you have metabolic models for multiple biological samples and

Use when you have preprocessed multi-class or time-course metabolomic

Use when you have generated hypothetical links (e.g., GCF–MF pairs) and

Use when you have an LC-HRMS feature table (m/z, retention time, isotope

Use when after cleaning and clustering LC-MS features in MS-CleanR, when

Use when you have multiple CSV feature tables from independent metabolomic

Use when you have loaded LC-MS feature tables or peak detection output

Use when you have raw or processed mass spectrometry data in HDF5 (.h5)

Use when you have two or more feature tables in HDF5 format with detected

Use when you have a parsed sample list with metadata (sample IDs, classification

Use when you have executed batch searches of MS/MS spectra against multiple

Use when your lipidomics dataset includes multiple experimental factors

Use when when evaluating a spectral embedding or compound identification

Use when you have raw metabolomics data files in one or more of the supported

'Use when after completing quality control, batch normalization, and

Use when you have metabolomics datasets from multiple studies that use

Use when the analytical goal requires detection of downstream transformation

Use when after performing an ANOVA-style multi-group de_design() analysis

Use when you have embedded sequences of chemical formulae (tokenized

Use when when building a transformer-based model to process mass spectrometry

Use when when you have an unknown tandem mass spectrum (MS/MS peaks with

Use when when you need to support multiple plotting library backends

Use when you have DIA mass spectrometry raw files from multiple instrument

Use when when converting tabular data to JSON via the matrix directive,

Use when you need to evaluate whether a newly released or candidate library

Use when you have a mass spectrum and a set of candidate molecular structures,

Use when you have acquired complementary spectroscopic measurements (NMR,

Use when after performing spot_align_byknn to map SM spots to ST spots,

Use when you have high-dimensional biological data (e.

Use when you have a set of molecular structures (as .sdf or .csv with

Use when when you have a pretrained encoder that captures domain knowledge

Use when you have raw or processed TWIM-MS data with arrival time and

Use when when you have matched transcriptomics (RNA-seq read counts),

Use when you have preprocessed and jointly normalized ST and SM data

Use when after completing pathway enrichment analysis on differentially

Use when when you have identifiers for two organisms available in KEGG

Use when when you need to visually compare two or more spectra (MS1,

Use when you have untargeted metabolomics data from multiple MS instruments

Use when you have paired microbiome-metabolome (or similar multivariate)

Use when after initial retention-time-based feature grouping (e.

Use when when you have MS1 mass spectrometry data from multiple samples

Use when you have two or more independently processed MemoMatrix objects

Use when you have two or more independent scoring functions ranking the

Use when your research software comprises multiple independent subprojects

Use when when building or modifying an asynchronous annotation pipeline

Use when you have metabolite identifiers sourced from a single metabolome