ReferenceSeeker determines closely related reference genomes following a scalable hierarchical approach combining an fast kmer profile-based database lookup of candidate reference genomes and subsequent computation of specific average nucleotide identity (ANI) values for the rapid determination of suitable reference genomes.
ReferenceSeeker computes kmer-based genome distances between a query genome and potential reference genome candidates via Mash (Ondov et al. 2016). For resulting candidates ReferenceSeeker subsequently computes (bidirectional) ANI values picking genomes meeting community standard thresholds by default (ANI >= 95 % & conserved DNA >= 69 %) (Goris, Konstantinos et al. 2007) ranked by the product of ANI and conserved DNA values to take into account both genome coverage and identity.
Custom databases can be built with local genomes. For further convenience, we provide pre-built databases with sequences from RefSeq (https://www.ncbi.nlm.nih.gov/refseq), GTDB and PLSDB copmrising the following taxa:
- bacteria
- archaea
- fungi
- protozoa
- viruses
as well as plasmids.
The reasoning for subsequent calculations of both ANI and conserved DNA values is that Mash distance values correlate well with ANI values for closely related genomes, however the same is not true for conserved DNA values. A kmer fingerprint-based comparison alone cannot distinguish if a kmer is missing due to a SNP, for instance or a lack of the kmer-comprising subsequence. As DNA conservation (next to DNA identity) is very important for many kinds of analyses, e.g. reference based SNP detections, ranking potential reference genomes based on a mash distance alone is often not sufficient in order to select the most appropriate reference genomes. If desired, ANI and conserved DNA values can be computed bidirectionally.
Path to a taxon database and a draft or finished genome in (zipped) fasta format:
$ referenceseeker ~/bacteria GCF_000013425.1.fnaTab separated lines to STDOUT comprising the following columns:
Unidirectionally (query -> references):
- RefSeq Assembly ID
- Mash Distance
- ANI
- Conserved DNA
- NCBI Taxonomy ID
- Assembly Status
- Organism
#ID Mash Distance ANI Con. DNA Taxonomy ID Assembly Status Organism
GCF_000013425.1 0.00000 100.00 100.00 93061 complete Staphylococcus aureus subsp. aureus NCTC 8325
GCF_001900185.1 0.00002 100.00 99.89 46170 complete Staphylococcus aureus subsp. aureus HG001
GCF_900475245.1 0.00004 100.00 99.57 93061 complete Staphylococcus aureus subsp. aureus NCTC 8325 NCTC8325
GCF_001018725.2 0.00016 100.00 99.28 1280 complete Staphylococcus aureus FDAARGOS_10
GCF_003595465.1 0.00185 99.86 96.81 1280 complete Staphylococcus aureus USA300-SUR6
GCF_003595385.1 0.00180 99.87 96.80 1280 complete Staphylococcus aureus USA300-SUR2
GCF_003595365.1 0.00180 99.87 96.80 1280 complete Staphylococcus aureus USA300-SUR1
GCF_001956815.1 0.00180 99.87 96.80 46170 complete Staphylococcus aureus subsp. aureus USA300_SUR1
...Bidirectionally (query -> references [QR] & references -> query [RQ]):
- RefSeq Assembly ID
- Mash Distance
- QR ANI
- QR Conserved DNA
- RQ ANI
- RQ Conserved DNA
- NCBI Taxonomy ID
- Assembly Status
- Organism
#ID Mash Distance QR ANI QR Con. DNA RQ ANI RQ Con. DNA Taxonomy ID Assembly Status Organism
GCF_000013425.1 0.00000 100.00 100.00 100.00 100.00 93061 complete Staphylococcus aureus subsp. aureus NCTC 8325
GCF_001900185.1 0.00002 100.00 99.89 100.00 99.89 46170 complete Staphylococcus aureus subsp. aureus HG001
GCF_900475245.1 0.00004 100.00 99.57 99.99 99.67 93061 complete Staphylococcus aureus subsp. aureus NCTC 8325 NCTC8325
GCF_001018725.2 0.00016 100.00 99.28 99.95 98.88 1280 complete Staphylococcus aureus FDAARGOS_10
GCF_001018915.2 0.00056 99.99 96.35 99.98 99.55 1280 complete Staphylococcus aureus NRS133
GCF_001019415.2 0.00081 99.99 94.47 99.98 99.36 1280 complete Staphylococcus aureus NRS146
GCF_001018735.2 0.00096 100.00 94.76 99.98 98.58 1280 complete Staphylococcus aureus NRS137
GCF_003354885.1 0.00103 99.93 96.63 99.93 96.66 1280 complete Staphylococcus aureus 164
...ReferenceSeeker can be installed via Conda and Git(Hub). In either case, a taxon database must be downloaded which we provide for download at Zenodo: 
The preferred way to install and run ReferenceSeeker is Conda using the Bioconda channel:
$ conda install -c bioconda referenceseeker
$ referenceseeker --helpAlternatively, you can use this raw GitHub repository:
- install necessary Python dependencies (if necessary)
- clone the latest version of the repository
- install necessary 3rd party executables (Mash, MUMmer4)
$ pip3 install --user biopython xopen
$ git clone https://github.com/oschwengers/referenceseeker.git
$ # install Mash & MUMmer
$ ./referenceseeker/bin/referenceseeker --helpTo test your installation we prepared a tiny mock database comprising 4 Salmonella spp genomes and a query assembly (SRA: SRR498276) in the tests directory:
$ git clone https://github.com/oschwengers/referenceseeker.git
# GitHub installation
$ ./referenceseeker/bin/referenceseeker referenceseeker/test/db referenceseeker/test/data/Salmonella_enterica_CFSAN000189.fasta
# BioConda installation
$ referenceseeker referenceseeker/test/db referenceseeker/test/data/Salmonella_enterica_CFSAN000189.fastaExpected output:
#ID Mash Distance ANI Con. DNA Taxonomy ID Assembly Status Organism
GCF_000439415.1 0.00003 100.00 99.55 1173427 complete Salmonella enterica subsp. enterica serovar Bareilly str. CFSAN000189
GCF_900205275.1 0.01522 98.61 83.13 90370 complete Salmonella enterica subsp. enterica serovar TyphiUsage:
usage: referenceseeker [--crg CRG] [--ani ANI] [--conserved-dna CONSERVED_DNA]
[--unfiltered] [--bidirectional] [--help] [--version]
[--verbose] [--threads THREADS]
<database> <genome>
Rapid determination of appropriate reference genomes.
positional arguments:
<database> ReferenceSeeker database path
<genome> target draft genome in fasta format
Filter options / thresholds:
These options control the filtering and alignment workflow.
--crg CRG, -r CRG Max number of candidate reference genomes to pass kmer
prefilter (default = 100)
--ani ANI, -a ANI ANI threshold (default = 0.95)
--conserved-dna CONSERVED_DNA, -c CONSERVED_DNA
Conserved DNA threshold (default = 0.69)
--unfiltered, -u Set kmer prefilter to extremely conservative values
and skip species level ANI cutoffs (ANI >= 0.95 and
conserved DNA >= 0.69
--bidirectional, -b Compute bidirectional ANI/conserved DNA values
(default = False)
Runtime & auxiliary options:
--help, -h Show this help message and exit
--version, -V show program's version number and exit
--verbose, -v Print verbose information
--threads THREADS, -t THREADS
Number of used threads (default = number of available
CPU cores)Installation:
$ conda install -c bioconda referenceseeker
$ wget https://zenodo.org/record/4415843/files/bacteria-refseq.tar.gz
$ tar -xzf bacteria-refseq.tar.gz
$ rm bacteria-refseq.tar.gzSimple:
$ # referenceseeker <REFERENCE_SEEKER_DB> <GENOME>
$ referenceseeker bacteria-refseq/ genome.fastaExpert: verbose output and increased output of candidate reference genomes using a defined number of threads:
$ # referenceseeker --crg 500 --verbose --threads 8 <REFERENCE_SEEKER_DB> <GENOME>
$ referenceseeker --crg 500 --verbose --threads 8 bacteria-refseq/ genome.fastaReferenceSeeker depends on databases comprising taxonomic genome informations as well as kmer hash profiles for each entry.
We provide pre-built databases based on public genome data hosted at Zenodo:
release: 221 (2024-01-09)
| Taxon | URL | # Genomes | Size |
|---|---|---|---|
| bacteria | https://zenodo.org/record/4415843/files/bacteria-refseq.tar.gz | 50,226 | 59.6 Gb |
| archaea | https://zenodo.org/record/4415843/files/archaea-refseq.tar.gz | 905 | 897 Mb |
| fungi | https://zenodo.org/record/4415843/files/fungi-refseq.tar.gz | 557 | 5.9 Gb |
| protozoa | https://zenodo.org/record/4415843/files/protozoa-refseq.tar.gz | 90 | 1.1 Gb |
| viruses | https://zenodo.org/record/4415843/files/viral-refseq.tar.gz | 14,012 | 1 Mb |
release: v214 (2024-01-11)
| Taxon | URL | # Genomes | Size |
|---|---|---|---|
| bacteria | n.a. due to storage quota resitrctions | 80,789 | 82 Gb |
| archaea | https://zenodo.org/record/4415843/files/archaea-gtdb.tar.gz | 4,416 | 2.8 Gb |
In addition to the genome based databases, we provide the following plasmid databases based on RefSeq and PLSDB:
| DB | URL | # Plasmids | Size |
|---|---|---|---|
| RefSeq | https://zenodo.org/record/4415843/files/plasmids-refseq.tar.gz | 81,674 | 2.6 Gb |
| PLSDB | https://zenodo.org/record/4415843/files/plasmids-plsdb.tar.gz | 59,882 | 2.3 Gb |
If above mentiond RefSeq based databases do not contain sufficiently-close related genomes or are just too large, ReferenceSeeker provides auxiliary commands in order to either create databases from scratch or to expand existing ones. Therefore, a second executable referenceseeker_db accepts init and import subcommands:
Usage:
usage: referenceseeker_db [--help] [--version] {init,import} ...
Rapid determination of appropriate reference genomes.
positional arguments:
{init,import} sub-command help
init Initialize a new database
import Add a new genome to database
Runtime & auxiliary options:
--help, -h Show this help message and exit
--version, -V show program's version number and exitIf a new database should be created, use referenceseeker_db init:
usage: referenceseeker_db init [-h] [--output OUTPUT] --db DB
optional arguments:
-h, --help show this help message and exit
--output OUTPUT, -o OUTPUT
output directory (default = current working directory)
--db DB, -d DB Name of the new ReferenceSeeker databaseThis new database or an existing one can be used to import genomes in Fasta, GenBank or EMBL format:
usage: referenceseeker_db import [-h] --db DB --genome GENOME [--id ID]
[--taxonomy TAXONOMY]
[--status {complete,chromosome,scaffold,contig}]
[--organism ORGANISM]
optional arguments:
-h, --help show this help message and exit
--db DB, -d DB ReferenceSeeker database path
--genome GENOME, -g GENOME
Genome path [Fasta, GenBank, EMBL]
--id ID, -i ID Unique genome identifier (default sequence id of first
record)
--taxonomy TAXONOMY, -t TAXONOMY
Taxonomy ID (default = 12908 [unclassified sequences])
--status {complete,chromosome,scaffold,contig}, -s {complete,chromosome,scaffold,contig}
Assembly level (default = contig)
--organism ORGANISM, -o ORGANISM
Organism name (default = "NA")Example:
If ReferenceSeeker is properly installed, clone this repository and change into its parent directoriy.
$ git clone https://github.com/oschwengers/referenceseeker.git
$ cd referenceseeker
$ referenceseeker_db init --db test-db --output ./
$ referenceseeker_db import --db ./test-db --genome test/db/GCF_000439415.1.fna.gz --id GCF_000439415.1 --taxonomy 28901 --status complete --organism "Salmonella enterica subsp. enterica serovar Bareilly str. CFSAN000189"
$ referenceseeker_db import --db ./test-db --genome test/db/GCF_002211925.1.fna.gz --id GCF_002211925.1 --organism "Salmonella bongori str. SA19983605"
$ referenceseeker -v ./test-db ./test/data/Salmonella_enterica_CFSAN000189.fasta
ReferenceSeeker needs the following dependencies:
- Python (3.8, 3.9), Biopython (>=1.78), xopen(>=1.1.0)
- Mash (2.3) https://github.com/marbl/Mash
- MUMmer (4.0.0-beta2) https://github.com/gmarcais/mummer
ReferenceSeeker has been tested against aforementioned versions.
Schwengers et al., (2020). ReferenceSeeker: rapid determination of appropriate reference genomes. Journal of Open Source Software, 5(46), 1994, https://doi.org/10.21105/joss.01994
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