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RdRp Collaborative Analysis Tool with Collections of pHMMs

RdRpCATCH - the RdRp Collaborative Analysis Tool with Collections of pHMMs represents a collaborative effort to consolidate various publicly available RdRp pHMM resources into a single, user-friendly platform. RdRpCATCH allows for seamless scanning of metatranscriptomics assemblies for RNA virus discovery and provides follow-up taxonomic annotation of the detected contigs.

How It Works

Complete workflow overview

RdRpCATCH Workflow Diagram

Figure 1: RdRpCATCH workflow overview showing the complete analysis pipeline

Key Features

Discover the key features of RdRpCATCH

Comprehensive Databases

Access and use multiple curated RdRp pHMM databases specialized for comprehensive RNA virus detection.

Easy Upload

Simple drag-and-drop interface for FASTA files. Supports both nucleotide and protein sequences.

Coverage metrics

Calculation of contig and profile coverage offer valuable insights into the RdRp completeness.

Taxonomic Annotation

Automatic taxonomic classification of detected contigs using an NCBI RefSeq Riboviria protein database and mmseqs2.

Comprehensive Results

Download detailed results including annotated sequences, taxonomic classifications, and visualization plots for further analysis.

Secure & Reliable

Your data is processed securely with automatic cleanup. Results are available for 7 days with secure access links.

Resources & Downloads

Access additional resources and command-line tools

GitHub Repository

Access the complete source code, documentation, and command-line version of RdRpCATCH for advanced users and developers.

View Repository

Zenodo Archive

Download the complete tool package including databases, scripts, and documentation for offline use.

Download Package

RdRp Summit Community

RdRpCATCH emerged as a collaborative project from the global RdRp Summit community. Join the community at rdrp.io for more information about the RdRp Summit, Slack, and Journal Club.

Visit rdrp.io

Citation

If you use RdRpCATCH in your research, please cite RdRpCATCH and the underlying databases:

Karapliafis, D., Neri, U., Olendraite, I., Charon, J., Sakaguchi, S., Hou, X., De Ridder, D., Zwart, M. P., & Kupczok, A. (2026). RdRpCATCH: A unified resource for RNA virus discovery using viral RNA-dependent RNA polymerase profile Hidden Markov models. BioRxiv. https://doi.org/10.64898/2026.02.05.703936

Our platform supports the following databases:


1. Lucaprot_HMM: Hou, X. and He, Y. et al. (2024) 'Using artificial intelligence to document the hidden RNA virosphere', Cell, 187(24). doi:10.1016/j.cell.2024.09.027
2. NeoRdRp: Sakaguchi, S. et al. (2022) 'NeoRdRp: A comprehensive dataset for identifying RNA-dependent RNA polymerases of various RNA viruses from metatranscriptomic data', Microbes and Environments, 37(3). doi:10.1264/jsme2.me22001
3. Neordrp2: Sakaguchi, S., Nakano, T. and Nakagawa, S. (2024) 'Neordrp2 with improved seed data, annotations, and scoring', Frontiers in Virology, 4. doi:10.3389/fviro.2024.1378695
4. RDRP-Scan: Charon, J. et al. (2022) 'RDRP-Scan: A bioinformatic resource to identify and annotate divergent RNA viruses in metagenomic sequence data', Virus Evolution, 8(2). doi:10.1093/ve/veac082
5. RVMT: Neri, U. et al. (2022) 'Expansion of the global RNA virome reveals diverse clades of bacteriophages', Cell, 185(21). doi:10.1016/j.cell.2022.08.023
6. Olendraite_fam: Olendraite, I. (2021) 'Mining diverse and novel RNA viruses in transcriptomic datasets', Apollo. Link
7. Olendraite_gen: Olendraite, I., Brown, K. and Firth, A.E. (2023) 'Identification of RNA virus–derived rdrp sequences in publicly available transcriptomic data sets', Molecular Biology and Evolution, 40(4). doi:10.1093/molbev/msad060
8. Zayed_HMM: Zayed, A. A., et al. (2022) 'Cryptic and abundant marine viruses at the evolutionary origins of Earth’s RNA virome.' Science, 376(6589), 156–162. doi:10.1126/science.abm5847

Need Help?

Have questions about RdRpCATCH or need support with your analysis?