pip install sourmash_plugin_pangenomics
You can run all of these commands in the test_workflow
directory of the git repository.
(CTB: explain contents!)
The following command builds a pangenome database for the species present in the lineages file gtdb-rs214-agatha.lineages.csv.gz
(currently only s__Agathobacter faecis
), using the sketches present in the gtdb-rs214-agatha-k21.zip
.
sourmash scripts pangenome_createdb \
gtdb-rs214-agatha-k21.zip \
-t gtdb-rs214-agatha.lineages.csv.gz \
-o agatha-merged.sig.zip --abund -k 21
The output file is agatha-merged.sig.zip
and contains the following:
% sourmash sig summarize agatha-merged.sig.zip
...
num signatures: 1
** examining manifest...
total hashes: 27398
summary of sketches:
1 sketches with DNA, k=21, scaled=1000, abund 27398 total hashes
Note: the command pangenome_merge
(see below) will construct a pangenome
sketch by merging all provided signatures.
A "ranktable" is our name for a database that assigns hashes a pangenomic "rank" - central core, external core, shell, inner cloud, or surface cloud.
The following command builds a ranktable for the species s__Agathobacter faecis
, selected from the pangenome database created above:
sourmash scripts pangenome_ranktable \
agatha-merged.sig.zip \
-o test_output/agathobacter_faecis.csv \
-k 21 -l 'GCF_020557615 s__Agathobacter faecis'
The output file is test_output/agathobacter_faecis.csv
, and it contains two columns:
hashval,pangenome_classification
96834755571756,1
119187685848053,1
129679169912030,1
...
18440589591308259,4
18443409651295626,4
18446214016691046,4
where the first column is the hash value, and the second column is the pangenome rank for that hash.
We can now use our ranktable to summarize any sketch, including a metagenome. Here we use a human gut metagenome, SRR5650070
:
sourmash scripts pangenome_classify \
SRR5650070.trim.sig.zip \
test_output/agathobacter_faecis.csv \
-k 21
This will yield the following output:
For 'test_output/agathobacter_faecis.csv', signature 'SRR5650070' contains:
497 (12.5%) hashes are classified as central core
427 (10.8%) hashes are classified as external core
1791 (45.2%) hashes are classified as shell
1251 (31.5%) hashes are classified as inner cloud
0 (0.0%) hashes are classified as surface cloud
...and 262716 hashes are NOT IN the csv file
(CTB: explain contents!)
The following command builds a pangenome sketch by combining all provided sketches. Here we use the sketches present in the gtdb-rs214-agatha-k21.zip
file:
sourmash scripts pangenome_merge \
gtdb-rs214-agatha-k21.zip \
-o agatha-merged-2.sig.zip-k 21
The output file is agatha-merged-2.sig.zip
and is identical
(via e.g. sourmash compare
) to the agatha-merged.sig.zip
file.
We suggest filing issues in the main sourmash issue tracker as that receives more attention (and is monitored by the same people anyway)!
sourmash_plugin_pangenomics
is developed at https://github.com/sourmash-bio/sourmash_plugin_pangenomics.
The current tests are implemented as Snakemake workflow in test_workflow/
. To run them, execute the following command in the main directory:
make cleanrun
Bump version number in pyproject.toml
and push.
Make a new release on github.
Then pull, and:
python -m build
followed by twine upload dist/...
.