Which de novo assembly algorithm is best for my data?

There are a number of assemblers available in Geneious. Some assemblers are not bundled with Geneious but may be installed as optional plugins from Tools -> Plugins. The best assembler to use may depend on your data. Below is a brief overview of the advantages and disadvantages of some assemblers.
 
Geneious
 
      Advantages:
            - Produces large contigs
            - Produces contigs containing reads
            - Can produce list of unused reads
            - Can produce circular contigs
 
      Disadvantages:
            - Slow (not feasible to use on genomes over 100 Mbp)
            - High memory usage

Tadpole (Available in Geneious R9 onwards)
 
      Advantages:
            - Extremely fast
            - Very low mis-assembly rate
 
      Disadvantages:
            - Produces only consensus sequences
            - May produce shorter contigs
            - May not work as well on gappy error models (e.g. 454, IonTorrent, PacBio)
            - Does not produce scaffolds

 

SPAdes (Available in Geneious R10.1 onwards)
      Advantages:
            - Produces long and accurate contigs
            - Works with many data types (e.g. Nanopore MinION, PacBio)
            - Supports RNA and metagenome data
 
      Disadvantages:
            - Produces only consensus sequences
            - Doesn't work with low coverage
            - Not designed for large genomes


Velvet
 
      Advantages:
            - Fast
            - Widely used
 
      Disadvantages:
            - Produces only consensus sequences
            - May not work as well on gappy error models (e.g. 454, IonTorrent, PacBio)

MIRA

      Advantages:
            - Works very well on bacterial genomes
            - Produces large contigs
            - Produces contigs containing reads
 
      Disadvantages:
            - Not feasible to use on large genomes     

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