First, create a blast+ database: makeblastdb -in <my_seqs.fna> -dbtype nucl -out <my_db>
Next, use megablast from blast+ package to perform all-vs-all blastn of sequences: blastn -query <my_seqs.fna> -db <my_db> -outfmt '6 std qlen slen' -max_target_seqs 10000 -o <my_blast.tsv> -num_threads 32
Note: using the -perc_identity flag will speed up the search at the cost of sensitivity: blastn -query <my_seqs.fna> -db <my_db> -outfmt '6 std qlen slen' -max_target_seqs 10000 -perc_identity 90 -o <my_blast.tsv> -num_threads 32
Next, calculate pairwise ANI by combining local alignments between sequence pairs: anicalc.py -i <my_blast.tsv> -o <my_ani.tsv>
Finally, perform UCLUST-like clustering using the MIUVIG recommended-parameters (95% ANI + 85% AF): aniclust.py --fna <my_seqs.fna> --ani <my_ani.tsv> --out <my_clusters.tsv> --min_ani 95 --min_tcov 85 --min_qcov 0
