skani basic usage guide

skani sketch - storing sketches/indices on disk

Note

skani sketch behaviour has changed in version v0.3 (August 2025). This manual is for >= v0.3.

# sketch genomes, output searchable database
skani sketch genome1.fa genome2.fa ... -o sketch_folder -t 20
skani search -d sketch_folder my_genome_query.fasta

# make individual, pre-indexed sketches
skani sketch --separate-sketches genome1.fa genome2.fa -o sketch_folder
skani dist sketch_folder/genome1.fa.sketch sketch_folder/genome2.fa.sketch

sketch computes a sketch (i.e., an index) of a set of genomes. This index is searchable in a memory efficient manner with search.

Alternatively, sketch --separate-files creates a .sketch file for each each input genome.fa. The .sketch files can be used as faster drop-in substitutes for fasta files.

skani dist - simple ANI calculation

# query each individal record in a multi-fasta (--qi for query, --ri for reference)
skani dist --qi -q query1.fa -r ref1.fa

# use lists of fastas, one line per fasta
skani dist --rl ref_list.txt --ql query_list.txt

# estimate confidence interval
skani dist --ci query1.fa ref1.fa

# turn off the ANI debiasing step
skani dist query1.fa ref1.fa --no-learned-ani

# only compare small contigs with >= 90% estimated ANI 
# use -m 300 for better filtering on small contigs
skani dist --qi query.fa --ri ref.fa -s 90 -m 300

dist computes ANI between all queries and all references. dist loads all reference and query genomes into memory.

If you're searching against a database, search can use much less memory (see below).

If you want to do all-to-all comparisons for the same set of genomes g1.fa g2.fa g3.fa, use skani triangle g1.fa g2.fa g3.fa -E instead of skani dist -q g1.fa g2.fa g3.fa -r g1.fa g2.fa g3.fa. triangle is 2x faster.

See the advanced usage guide for information on optimally using skani when

• genomes are small (-m parameter becomes important)
• genomes are very fragmented (-c becomes important)
• and more.

skani search - memory-efficient ANI database queries

# any algorithm options used in "sketch" will also be used for searching. 
skani sketch genome1.fa genome2.fa ... -o database

# query query1.fa, query2.fa, ... against sketches in sketch_folder
skani search -d database query1.fa query2.fa ...  -o output.txt

search is a memory efficient method of calculating ANI against a large reference database. Searching one gneome against ~65000 genomes takes only 6 GB of memory using search. This is achieved by only loading genomes that pass a filter into memory, then discarding the genome after each query is done.

The parameters for search are obtained from the parameters used for the sketch option, so if you sketch with say -c 60 for the sketch option, this will be implied in the search option.

If you're querying many sequences, the file I/O step will dominate the running time, so consider using dist instead if you have enough RAM.

skani triangle - all-to-all ANI computation

# all-to-all ANI comparison in lower-triangular matrix
skani triangle genome1.fa genome2.fa genome3.fa -o lower_triangle_matrix.txt

# output sparse matrix a.k.a an edge list of comparisons
skani triangle -l list_of_genomes.txt -o sparse_matrix.txt --sparse 

# output square matrix
skani triangle genome1.fa genome2.fa genome3.fa --full-matrix 

triangle outputs a lower-triangular matrix in phyllip format. The ANI is output to stdout or the file specified. The aligned fraction is also output in a separate file with the suffix .af attached.

triangle avoids doing n^2 computations and only does n(n-1)/2 computations as opposed to dist, so it is more efficient. It also sets some smarter default parameters for all-to-all search.

For very large data sets, use -E or --sparse instead, which only outputs non-zero entries in an edge-list output.

triangle loads all genome indices into memory. For doing comparisons on massive data sets, see the Advanced section for suggestions on reducing memory cost.