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Using sourmash from the command line

From the command line, sourmash can be used to compute MinHash sketches from DNA sequences, compare them to each other, and plot the results; these sketches are saved into "signature files". These signatures allow you to estimate sequence similarity quickly and accurately in large collections, among other capabilities.

Please see the mash software and the mash paper (Ondov et al., 2016) for background information on how and why MinHash sketches work.

sourmash uses a subcommand syntax, so all commands start with sourmash followed by a subcommand specifying the action to be taken.

An example

Grab three bacterial genomes from NCBI:

curl -L -O ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/bacteria/Escherichia_coli/reference/GCF_000005845.2_ASM584v2/GCF_000005845.2_ASM584v2_genomic.fna.gz
curl -L -O ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/bacteria/Salmonella_enterica/reference/GCF_000006945.1_ASM694v1/GCF_000006945.1_ASM694v1_genomic.fna.gz
curl -L -O ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/bacteria/Sphingobacteriaceae_bacterium_DW12/latest_assembly_versions/GCF_000783305.1_ASM78330v1/GCF_000783305.1_ASM78330v1_genomic.fna.gz

Compute signatures for each:

   sourmash compute *.fna.gz

This will produce three .sig files containing MinHash signatures at k=31.

Next, compare all the signatures to each other:

sourmash compare *.sig -o cmp

Finally, plot a dendrogram:

sourmash plot cmp

This will output two files, cmp.dendro.png and cmp.matrix.png, containing a clustering & dendrogram of the sequences, as well as a similarity matrix and heatmap.

Matrix:

Matrix

The sourmash command and its subcommands

To get a list of subcommands, run sourmash without any arguments.

There are five main subcommands: compute, compare, plot, search, and gather. See the tutorial for a walkthrough of these commands.

  • compute creates signatures.
  • compare compares signatures and builds a distance matrix.
  • plot plots distance matrices created by compare.
  • search finds matches to a query signature in a collection of signatures.
  • gather finds non-overlapping matches to a metagenome in a collection of signatures.

There are also a number of commands that work with taxonomic information; these are grouped under the sourmash lca subcommand. See the LCA tutorial for a walkthrough of these commands.

  • lca classify classifies many signatures against an LCA database.
  • lca summarize summarizes the content of a metagenome using an LCA database.
  • lca gather finds non-overlapping matches to a metagenome in an LCA database.
  • lca index creates a database for use with LCA subcommands.
  • lca rankinfo summarizes the content of a database.
  • lca compare_csv compares lineage spreadsheets, e.g. those output by lca classify.

Finally, there are a number of utility and information commands:

  • info shows version and software information.
  • index indexes many signatures using a Sequence Bloom Tree (SBT).
  • sbt_combine combines multiple SBTs.
  • categorize is an experimental command to categorize many signatures.
  • watch is an experimental command to classify a stream of sequencing data.

sourmash compute

The compute subcommand computes and saves signatures for each sequence in one or more sequence files. It takes as input FASTA or FASTQ files, and these files can be uncompressed or compressed with gzip or bzip2. The output will be one or more JSON signature files that can be used with sourmash compare.

Please see Using sourmash: a practical guide for more information on computing signatures.


Usage:

sourmash compute filename [ filename2 ... ]

Optional arguments:

--ksizes K1[,K2,K3] -- one or more k-mer sizes to use; default is 31
--force -- recompute existing signatures; convert non-DNA characters to N
--output -- save all the signatures to this file; can be '-' for stdout.
--track-abundance -- compute and save k-mer abundances.
--name-from-first -- name the signature based on the first sequence in the file
--singleton -- instead of computing a single signature for each input file,
               compute one for each sequence
--merged <name> -- compute a single signature for all of the input files,
                   naming it <name>

sourmash compare

The compare subcommand compares one or more signature files (created with compute) using estimated Jaccard index. The default output is a text display of a similarity matrix where each entry [i, j] contains the estimated Jaccard index between input signature i and input signature j. The output matrix can be saved to a file with --output and used with the sourmash plot subcommand (or loaded with numpy.load(...). Using --csv will output a CSV file that can be loaded into other languages than Python, such as R.

Usage:

sourmash compare file1.sig [ file2.sig ... ]

Options:

--output -- save the distance matrix to this file (as a numpy binary matrix)
--ksize -- do the comparisons at this k-mer size.

sourmash plot

The plot subcommand produces two plots -- a dendrogram and a dendrogram+matrix -- from a distance matrix computed by sourmash compare --output <matrix>. The default output is two PNG files.

Usage:

sourmash plot <matrix>

Options:

--pdf -- output PDF files.
--labels -- display the signature names (by default, the filenames) on the plot
--indices -- turn off index display on the plot.
--vmax -- maximum value (default 1.0) for heatmap.
--vmin -- minimum value (default 0.0) for heatmap.
--subsample=<N> -- plot a maximum of <N> samples, randomly chosen.
--subsample-seed=<seed> -- seed for pseudorandom number generator.

Example output:

An E. coli comparison plot

sourmash search

The search subcommand searches a collection of signatures or SBTs for matches to the query signature. It can search for matches with either high Jaccard similarity or containment; the default is to use Jaccard similarity, unless --containment is specified. -o/--output will create a CSV file containing the matches.

search will load all of provided signatures into memory, which can be slow and somewhat memory intensive for large collections. You can use sourmash index to create a Sequence Bloom Tree (SBT) that can be quickly searched on disk; this is the same format in which we provide GenBank and other databases.

Usage:

sourmash search query.sig [ list of signatures or SBTs ]

Example output:

49 matches; showing first 20:
similarity   match
----------   -----
 75.4%       NZ_JMGW01000001.1 Escherichia coli 1-176-05_S4_C2 e117605...
 72.2%       NZ_GG774190.1 Escherichia coli MS 196-1 Scfld2538, whole ...
 71.4%       NZ_JMGU01000001.1 Escherichia coli 2-011-08_S3_C2 e201108...
 70.1%       NZ_JHRU01000001.1 Escherichia coli strain 100854 100854_1...
 69.0%       NZ_JH659569.1 Escherichia coli M919 supercont2.1, whole g...
...    

sourmash gather

The gather subcommand finds all non-overlapping matches to the query. This is specifically meant for metagenome and genome bin analysis. (See Classifying Signatures for more information on the different approaches that can be used here.)

If the input signature was computed with --track-abundance, output will be abundance weighted (unless --ignore-abundances is specified). -o/--output will create a CSV file containing the matches.

gather, like search, will load all of provided signatures into memory. You can use sourmash index to create a Sequence Bloom Tree (SBT) that can be quickly searched on disk; this is the same format in which we provide GenBank and other databases.

Usage:

sourmash gather query.sig [ list of signatures or SBTs ]

Example output:

overlap     p_query p_match 
---------   ------- --------
1.4 Mbp      11.0%   58.0%      JANA01000001.1 Fusobacterium sp. OBRC...
1.0 Mbp       7.7%   25.9%      CP001957.1 Haloferax volcanii DS2 pla...
0.9 Mbp       7.4%   11.8%      BA000019.2 Nostoc sp. PCC 7120 DNA, c...
0.7 Mbp       5.9%   23.0%      FOVK01000036.1 Proteiniclasticum rumi...
0.7 Mbp       5.3%   17.6%      AE017285.1 Desulfovibrio vulgaris sub...

Note:

Use sourmash gather to classify a metagenome against a collection of genomes with no (or incomplete) taxonomic information. Use sourmash lca summarize and sourmash lca gather to classify a metagenome using a collection of genomes with taxonomic information.

sourmash lca subcommands

These commands use LCA databases (created with lca index, below, or prepared databases such as genbank-k31.lca.json.gz).

sourmash lca classify

sourmash lca classify classifies one or more signatures using the given list of LCA DBs. It is meant for classifying metagenome-assembled genome bins (MAGs) and single-cell genomes (SAGs).

Usage:

sourmash lca classify --query query.sig [query2.sig ...] --db <lca db> [<lca db2> ...]

For example, the command

sourmash lca classify --query tests/test-data/63.fa.sig \
    --db podar-ref.lca.json 

will produce the following logging to stderr:

loaded 1 LCA databases. ksize=31, scaled=10000
finding query signatures...
outputting classifications to stdout
... classifying NC_011663.1 Shewanella baltica OS223, complete genome
classified 1 signatures total

and the example classification output is a CSV file with headers:

ID,status,superkingdom,phylum,class,order,family,genus,species
"NC_009665.1 Shewanella baltica OS185, complete genome",found,Bacteria,Proteobacteria,Gammaproteobacteria,Alteromonadales,Shewanellaceae,Shewanella,Shewanella baltica

The status column in the classification output can take three possible values: nomatch, found, and disagree. nomatch means that no match was found for this query, and found means that an unambiguous assignment was found - all k-mers were classified within the same taxonomic hierarchy, and the most detailed lineage available was reported. disagree means that there was a taxonomic disagreement, and the lowest compatible taxonomic node was reported.

To elaborate on this a bit, suppose that all of the k-mers within a signature were classified as family Shewanellaceae, genus Shewanella, or species Shewanella baltica. Then the lowest compatible node (here species Shewanella baltica) would be reported, and the status of the classification would be found. However, if a number of additional k-mers in the input signaturer were classified as Shewanella oneidensis, sourmash would be unable to resolve the taxonomic assignment below genus Shewanella and it would report a status of disagree with the genus-level assignment of Shewanella; species level assignments would not be reported.

(This is the approach that Kraken and other lowest common ancestor implementations use, we believe.)

sourmash lca summarize

sourmash lca summarize produces a Kraken-style summary of the combined contents of the given query signatures. It is meant for exploring metagenomes and metagenome-assembled genome bins.

Note, unlike sourmash lca classify, lca summarize merges all of the query signatures into one and reports on the combined contents. This may be changed in the future.

Usage:

sourmash lca summarize --query query.sig [query2.sig ...] 
    --db <lca db> [<lca db2> ...]

For example, the command line:

sourmash lca summarize --query tests/test-data/63.fa.sig \
    --db tests/test-data/podar-ref.lca.json 

will produce the following log output to stderr:

loaded 1 LCA databases. ksize=31, scaled=10000
finding query signatures...
loaded 1 signatures from 1 files total.

and the following example summarize output to stdout:

50.5%   278   Bacteria;Proteobacteria;Gammaproteobacteria;Alteromonadales;Shewanellaceae;Shewanella;Shewanella baltica;Shewanella baltica OS223
100.0%   550   Bacteria;Proteobacteria;Gammaproteobacteria;Alteromonadales;Shewanellaceae;Shewanella;Shewanella baltica
100.0%   550   Bacteria;Proteobacteria;Gammaproteobacteria;Alteromonadales;Shewanellaceae;Shewanella
100.0%   550   Bacteria;Proteobacteria;Gammaproteobacteria;Alteromonadales;Shewanellaceae
100.0%   550   Bacteria;Proteobacteria;Gammaproteobacteria;Alteromonadales
100.0%   550   Bacteria;Proteobacteria;Gammaproteobacteria
100.0%   550   Bacteria;Proteobacteria
100.0%   550   Bacteria

The output is space-separated and consists of three columns: the perrcentage of total k-mers that have this classification; the number of k-mers that have this classification; and the lineage classification. K-mer classifications are reported hierarchically, so the percentages and totals contain all assignments that are at a lower taxonomic level - e.g. Bacteria, above, contains all the k-mers in Bacteria;Proteobacteria.

The same information is reported in a CSV file if -o/--output is used.

sourmash lca gather

The sourmash lca gather command finds all non-overlapping matches to the query, similar to the sourmash gather command. This is specifically meant for metagenome and genome bin analysis. (See Classifying Signatures for more information on the different approaches that can be used here.)

If the input signature was computed with --track-abundance, output will be abundance weighted (unless --ignore-abundances is specified). -o/--output will create a CSV file containing the matches.

Usage:

sourmash lca gather query.sig [<lca database> ...]

Example output:

overlap     p_query p_match
---------   ------- --------
1.8 Mbp      14.6%    9.1%      Fusobacterium nucleatum
1.0 Mbp       7.8%   16.3%      Proteiniclasticum ruminis
1.0 Mbp       7.7%   25.9%      Haloferax volcanii
0.9 Mbp       7.4%   11.8%      Nostoc sp. PCC 7120
0.9 Mbp       7.0%    5.8%      Shewanella baltica
0.8 Mbp       6.0%    8.6%      Desulfovibrio vulgaris
0.6 Mbp       4.9%   12.6%      Thermus thermophilus

sourmash lca index

The sourmash lca index command creates an LCA database from a lineage spreadsheet and a collection of signatures. This can be used to create LCA databases from private collections of genomes, and can also be used to create databases for e.g. subsets of GenBank.

See the sourmash lca tutorial and the blog post Why are taxonomic assignments so different for Tara bins? for some use cases.

If you are interested in preparing lineage spreadsheets from GenBank genomes (or building off of NCBI taxonomies more generally), please see the NCBI lineage repository.

sourmash lca rankinfo

The sourmash lca rankinfo command displays k-mer specificity information for one or more LCA databases. See the blog post How specific are k-mers for taxonomic assignment of microbes, anyway? for example output.

sourmash lca compare_csv

The sourmash lca compare_csv command compares two lineage spreadsheets (such as those output by sourmash lca classify or taken as input by sourmash lca index) and summarizes their agreement/disagreement. Please see the blog post Why are taxonomic assignments so different for Tara bins? for an example use case.