RDP5

RDP5 detects and characterizes recombination events within nucleotide sequence datasets to support molecular evolution and phylogenetic analyses.


Key Features:

  • Recombination detection: Automatically detects and characterizes recombination events in nucleotide sequence alignments.
  • Statistical testing: Incorporates statistical tests to distinguish true recombination signals from those potentially arising from other evolutionary processes.
  • Scalability: Processes alignments containing up to 5,000 sequences with sequence lengths up to 50 million sites.
  • Performance: Implements algorithmic enhancements delivering up to fivefold speed increases relative to RDP4.
  • Recombinant disassembly: Disassembles recombinant sequences into inferred parental components and produces recombination-free datasets in multiple alignment formats.
  • Manual verification and data management: Provides tools for manual verification of detected recombination events along with data management and visualization functions.

Scientific Applications:

  • Phylogenetic analysis: Identify and remove recombination signals to improve phylogenetic inference.
  • Molecular evolution: Generate recombination-free datasets for molecular evolution and comparative sequence analyses.
  • Recombination history exploration: Investigate and reconstruct recombination histories within nucleotide datasets.

Methodology:

Automated recombination detection using incorporated statistical tests to distinguish true recombination signals, algorithmic enhancements for increased processing speed, and disassembly of recombinant sequences into original components.

Topics

Details

Operating Systems:
Windows
Added:
11/29/2021
Last Updated:
11/29/2021

Operations

Publications

Martin DP, Varsani A, Roumagnac P, Botha G, Maslamoney S, Schwab T, Kelz Z, Kumar V, Murrell B. RDP5: a computer program for analyzing recombination in, and removing signals of recombination from, nucleotide sequence datasets. Virus Evolution. 2020;7(1). doi:10.1093/ve/veaa087. PMID:33936774. PMCID:PMC8062008.

PMID: 33936774
PMCID: PMC8062008
Funding: - Swedish Research Council: 1, 2018-

Documentation