Table 2.

Steps for ANI calculation based on ANI_BLASTN.

Step	Code/software
Step 1: Data preprocessing	average_nucleotide_identity.py -i fasta/ -o out_file -m ANIb -s 200—workers 10
Step 1: ANI calculation (performed by R script)	ani_alnlen = blast_alnlen- blast_gaps ani_alnids = blast_alnlen- blast_gaps- blast_mismatch ani_coverage = ani_alnlen /qlen ani_pid = ani_alnids/qlen ani_coverage > 0.7 & ani_pid > 0.3 & Delete the duplicate alignment ANIb_percentage_identity = ∑(ani_alnids * blast_pid)/∑ani_alnlen
Step 2: Data filtration	cat out.txt| awk ‘{if($3≥95) print $0}’ > 95filter.txt (similarity score cutoff: 95); cat out.txt| awk ‘{if($3≥98) print $0}’ > 98filter.txt (similarity score cutoff: 98)
Step 3: Visualization	Cytoscape