Referenceseeker
Rapid determination of appropriate reference genomes.
Install / Use
/learn @oschwengers/ReferenceseekerREADME
ReferenceSeeker: rapid determination of appropriate reference genomes
Contents
Description
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.
Input & Output
Input
Path to a taxon database and a draft or finished genome in (zipped) fasta format:
$ referenceseeker ~/bacteria GCF_000013425.1.fna
Output
Tab 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
...
Installation
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:
For more information have a look at Databases.
BioConda
The preferred way to install and run ReferenceSeeker is Conda using the Bioconda channel:
$ conda install -c bioconda referenceseeker
$ referenceseeker --help
GitHub
Alternatively, 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 --help
Test
To 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.fasta
Expected 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 Typhi
Usage
Usage:
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)
Examples
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.gz
Simple:
$ # referenceseeker <REFERENCE_SEEKER_DB> <GENOME>
$ referenceseeker bacteria-refseq/ genome.fasta
Expert: verbose output and increased output of candidate reference genomes using a defined number of threads:
