all methods related to Enterobase
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EToKi (Enterobase Tool Kit)

all methods related to Enterobase

External dependencies:

phylo module

  • raxml

prepare module

  • bbmap

MLSType module

  • blastn
  • usearch

assemble module

  • samtools
  • bwa
  • bowtie2
  • kraken
  • gatk
  • megahit
  • pilon
  • spades

ortho module

  • mcl
  • fasttree
  • vsearch

Python version: 2.7.9

Please read [] for python version control.

PIP Packages:

  • ete3==3.0.0b17
  • numpy==1.11.3
  • pandas==0.18.0
  • psutil==5.1.0


Assume all the external dependencies are in system PATH.

git clone
cd EToKi
pip install -r requirements.txt
python configure

Specify the links to external commands if they are not in the system PATH. Use

python configure -h

For additional information.

Usage: [options]

  configure        Configure external dependencies
  prepare          Preprocessing for short reads
  assemble         de novo / reference-guided asembly for either metagenomic or non-metagenomic reads
  ortho            Pan-genome prediction
  MLSTdb           Create database for MLST typing
  MLSType          MLST nomenclature
  phylo            Infer phylogeny and ancestral states from genomic alignments or SNP matrix
  RecHMM           Identify Recombination sketches.

Use <command> -h for help in each command.


1. phylogeny + ancestral reconstruction + recombination detection (phylo_example.bash)

cd examples
python ../ phylo -t all -p phylo_out -m phylo_rec.fasta
python ../ RecHMM -d phylo_out.mutations.gz -p rec_out

Outputs are:

  • examples/phylo_out.matrix.gz - a table of mutations in the alignment.
  • examples/phylo_out.labeled.nwk - phylogeny with labeled internal nodes.
  • examples/phylo_out.ancestral_states.gz - Ancestral states of internal nodes.
  • examples/phylo_out.mutations.gz - Occurences of mutations on different branches.
  • examples/ - Estimated parameters for the recombinations.
  • examples/rec_out.recombination.region - Identified recombination regions.

NOTE: New RecHMM identifies three categories of recombinations:

  1. External: Recombination with an external source. High SNP densities and low homoplasies.
  2. Internal: Recombination from an internal source. Normal SNP densities and high homoplasies.
  3. Mixed: Repetitive imports from external sources to different branches of the tree. High SNP densities and high homoplasies.

You can use legacy RecHMM by setting --task 0, which considers only external source.

2. short reads preprocess + assembly + polish + consensus quality + evaluation (assemble_example.bash)

cd examples
python ../ prepare --pe A_R1.fastq.gz,A_R2.fastq.gz -p prep_out
python ../ assemble --pe prep_out_L1_R1.fastq.gz,prep_out_L1_R2.fastq.gz --se prep_out_L1_R3.fastq.gz -p asm_out

Outputs are:

  • examples/prep_out_L1_R?.fastq.gz - Short reads after quality filtering
  • asm_out.result.fastq - Assembly with consensus quality information
  • asm_out.result.fasta - Assembly in fasta format

NOTE: example is copied from sample data in SPAdes 3.10