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Conduit is a scalable, modular workflow management system for metaproteomics data analysis. Built with Snakemake, it processes Data Independent Acquisition (DIA) mass spectrometry data and integrates with metagenomic data when available.
The ecosystem consists of:
- conduit-ascent — The core Snakemake workflow that handles computation and data processing.
- conduitR — An R package providing utility functions, data structures, and the Conduit object format used throughout the ecosystem.
- conduit-summit — An interactive R Shiny application for exploring Conduit outputs without writing code.
- conduit-basecamp - A graphical interface that gives the user a graphical interface to the entire conduit ecosystem.
One of the biggest challenges in metaproteomics is defining an appropriate search space. A well-defined search space reduces false positives and improves protein inference — but the best approach depends on what experimental data you have available.
Conduit is flexible: it supports multiple search space strategies so you can adapt whether or not you have metagenomic data. The supported methods are described below.
Another challenge is biological interpretation — turning peptide and protein data into meaningful insights. Conduit handles all functional annotation and summarizes information at every level: precursors, peptides, proteins, taxonomy, and function.
All results are stored in a standardized conduit.rds file — a Conduit object (built on QFeatures from conduitR) that retains annotations, database information, and QC metrics in a single portable R object ready for downstream analysis.
| Method | Config value | Best when... |
|---|---|---|
| NCBI Taxonomy IDs | ncbi_taxonomy_id |
You know which taxa are present but don't have genome data |
| UniProt Proteome IDs | uniprot_proteome_id |
You want to target a defined set of reference proteomes |
| Peptidotyping | peptidotyping |
No sequence data available — uses MS data directly to infer taxa |
| MetaPhlAn | metaphlan |
You have shotgun metagenomic FASTQ files |
| MAGs | MAGs |
You have metagenome-assembled genomes from your sample |