BioMate-KB Bioconductor Skills — 200 packages (top 100 by downloads + 100 rising stars) as vignette-grounded Claude/agent skills, with per-package workflow recipes
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed fu.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Utilities for microbiome analysis.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
This skill is the knowledge layer — when, why, and how to use phyloseq. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
The Bandle package enables the analysis and visualisation of differential localisation experiments using mass-spectrometry data. Experimental methods supported include dynamic LOPIT-DC, hyperLOPIT, Dynamic Organellar Maps, Dynamic PCP. It provides Bioconductor infrastructure to analyse these data.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Build, annotate, and analyze a protein-protein interaction (PPI) network to identify central proteins, functional communities, bridging proteins, and disease/annotation overlaps.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Provides utilities for identifying drug-target interactions for sets of small molecule or gene/protein identifiers. The required drug-target interaction information is obained from a local SQLite instance of the ChEMBL database. ChEMBL has been chosen for this purpose, because it provides one of the most comprehensive…
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Data quality assessment is an integral part of preparatory data analysis to ensure sound biological information retrieval. We present here the MatrixQCvis package, which provides shiny-based interactive visualization of data quality metrics at the per-sample and per-feature level. It is broadly applicable to…
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducin.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Mass spectrometry (MS) data backend supporting import and export of MS/MS library spectra from MassBank record files. Different backends are available that allow handling of data in plain MassBank text file format or allow also to interact directly with MassBank SQL databases. Objects from this package are supposed to…
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
MsCoreUtils defines low-level functions for mass spectrometry data and is independent of any high-level data structures. These functions include mass spectra processing functions (noise estimation, smoothing, binning, baseline estimation).
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
The MsDataHub package uses the ExperimentHub infrastructure to distribute raw mass spectrometry data files, peptide spectrum matches or quantitative data from proteomics and metabolomics experiments.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
A parser for mzIdentML files implemented using the XML package. The parser tries to be general and able to handle all types of mzIdentML files with the drawback of having less 'pretty' output than a vendor specific parser. Please contact th.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
This skill is the knowledge layer — when, why, and how to use mzr. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
PhIPData defines an S4 class for phage-immunoprecipitation sequencing (PhIP-seq) experiments. Buliding upon the RangedSummarizedExperiment class, PhIPData enables users to coordinate metadata with experimental data in analyses. Additionally, PhIPData provides specialized methods to subset and identify beads-only…
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
The PSMatch package helps proteomics practitioners to load, handle and manage Peptide Spectrum Matches. It provides functions to model peptide-protein relations as adjacency matrices and connected components, visualise these as graphs and m.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assa.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
This skill is the knowledge layer — when, why, and how to use stringdb. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
A first step in the data analysis of Mass Spectrometry (MS) based proteomics data is to identify peptides and proteins. With this respect the huge number of experimental mass spectra typically have to be assigned to theoretical peptides derived from a sequence database. Search engines are used for this purpose. These…
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
MEM, Marker Enrichment Modeling, automatically generates and displays quantitative labels for cell populations that have been identified from single-cell data. The input for MEM is a dataset that has pre-clustered or pre-gated populations with cells in rows and features in columns. Labels convey a list of measured…
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
A package for demultiplexing single-cell sequencing experiments of pooled cells labeled with barcode oligonucleotides. The package implements methods to fit regression mixture models for a probabilistic classification of cells, including multiplet detection. Demultiplexing error rates can be estimated, and methods for…
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Perform cellular neighborhood scanning, colocalization analysis, and neighborhood-based clustering on single-cell spatial transcriptomics data.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
Save MultiAssayExperiments to h5mu files supported by muon and mudata. Muon is a Python framework for multimodal omics data analysis. It uses an HDF5-based format for data storage.
bioMate-AI/biomate-bioconductor-kb
Skill Claude Code
A post hoc cell type classification tool to fine-tune cell type annotations generated by any cell type classification procedure with semi-supervised learning algorithm AdaSampling technique. The current version of scReClassify supports Support Vector Machine and Random Forest as a base classifier.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: