ReferenceSeeker: rapid determination of appropriate reference genomes.
Project description
ReferenceSeeker: rapid determination of appropriate reference genomes.
Contents
Description
ReferenceSeeker determines closely related reference genomes from RefSeq (https://www.ncbi.nlm.nih.gov/refseq) following a scalable hierarchical approach combining an ultra-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 and a database built on RefSeq genomes via Mash (Ondov et al. 2016). Therefore, only complete genomes or those stated as 'representative' or 'reference' genome are included. ReferenceSeeker offers pre-built databases for a broad spectrum of microbial taxonomic groups, i.e. bacteria, archaea, fungi, protozoa and viruses. For resulting candidates ReferenceSeeker subsequently computes ANI values picking genomes meeting community standard thresholds (ANI >= 95 % & conserved DNA >= 69 %) (Goris, Konstantinos et al. 2007) ranked by ANI and conserved DNA.
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 but 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 conservancy (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.
Input & Output
Input:
Path to a taxon database and a draft or finished genome in fasta format:
$ referenceseeker.py --db ~/bacteria GCF_000013425.1.fna
Output:
Tab separated lines to STDOUT comprising the following columns:
- RefSeq Assembly ID
- ANI
- Conserved DNA
- Mash Distance
- NCBI Taxonomy ID
- Assembly Status
- Organism
#ID ANI Con. DNA Mash Distance Taxonomy ID Assembly Status Organism
GCF_000013425.1 100.00 100.00 0.00000 93061 complete Staphylococcus aureus subsp. aureus NCTC 8325
GCF_001900185.1 100.00 99.89 0.00002 46170 complete Staphylococcus aureus subsp. aureus HG001
GCF_900475245.1 100.00 99.57 0.00004 93061 complete Staphylococcus aureus subsp. aureus NCTC 8325 NCTC8325
GCF_001018725.2 100.00 99.28 0.00016 1280 complete Staphylococcus aureus FDAARGOS_10
GCF_001018915.2 99.99 96.35 0.00056 1280 complete Staphylococcus aureus NRS133
...
Installation
To setup ReferenceSeeker just do the following:
- install necessary Python dependencies (if necessary)
- clone the latest version of the repository
- download and extract a databases or create one yourself
Example:
$ pip3 install biopython
$ git clone https://github.com/oschwengers/referenceseeker.git
$ wget https://zenodo.org/record/3562005/files/bacteria.tar.gz?download=1
$ tar -xzf bacteria.tar.gz
$ rm bacteria.tar.gz
Alternatively, use the aforementioned Docker image (oschwengers/referenceseeker) in order to ease the setup process.
Usage
Usage:
usage: referenceseeker [-h] [--crg CRG] [--unfiltered] [--verbose]
[--threads THREADS] [--version]
<database> <genome>
Rapid determination of appropriate reference genomes.
positional arguments:
<database> ReferenceSeeker database path
<genome> Target draft genome in fasta format
optional arguments:
-h, --help show this help message and exit
--crg CRG, -c CRG Max number of candidate reference genomes to assess
(default = 100)
--unfiltered, -u Set kmer prefilter to extremely conservative values
and skip species level ANI cutoffs (ANI >= 0.95 and
conserved DNA >= 0.69
--verbose, -v Print verbose information
--threads THREADS, -t THREADS
Number of threads to use (default = number of
available CPUs)
--version, -V show program's version number and exit
Examples
Simple:
$ bin/referenceseeker <REFERENCE_SEEKER_DB> <GENOME>
Expert: verbose output and increased output of candidate reference genomes using a defined number of threads:
$ bin/referenceseeker --crg 500 --verbose --threads 8 <REFERENCE_SEEKER_DB> <GENOME>
With Docker:
$ sudo docker pull oschwengers/referenceseeker:latest
$ sudo docker run --rm -v <REFERENCE_SEEKER_DB>:/db -v <DATA_DIR>:/data oschwengers/referenceseeker:latest <REFERENCE_SEEKER_DB> <GENOME>
With Docker shell script:
$ sudo docker pull oschwengers/referenceseeker:latest
$ referenceseeker.sh <REFERENCE_SEEKER_DB> <GENOME>
Databases
ReferenceSeeker depends on custom databases based on reference, representative as well as complete NCBI RefSeq genomes comprising kmer hash profiles and taxonomic information. We provide the following pre-built databases based on RefSeq 2019-07-02 via :
Taxon | URL | # Genomes | Size Zipped | Size Unzipped |
---|---|---|---|---|
bacteria | https://zenodo.org/record/3562005/files/bacteria.tar.gz?download=1 | 18,229 | 22 Gb | 71 Gb |
archaea | https://zenodo.org/record/3562005/files/archaea.tar.gz?download=1 | 417 | 364 Mb | 1.2 Gb |
fungi | https://zenodo.org/record/3562005/files/fungi.tar.gz?download=1 | 288 | 2.6 Gb | 8 Gb |
protozoa | https://zenodo.org/record/3562005/files/protozoa.tar.gz?download=1 | 88 | 1 Gb | 3.4 Gb |
viral | https://zenodo.org/record/3562005/files/viral.tar.gz?download=1 | 9,264 | 608 Mb | 835 Mb |
Updated database versions reflecting the latest RefSeq versions can be built with a shell script and nextflow pipeline.
Download and install Nextflow:
$ curl -fsSL get.nextflow.io | bash
Build database:
$ export REFERENCE_SEEKER_HOME=<REFERENCE_SEEKER_DIR>
$ sh $REFERENCE_SEEKER_HOME/build-db.sh <DB_TYPE_OPTION>
List of available database options:
$ sh build-db.sh
-b (bacteria)
-a (archaea)
-v (viral)
-f (fungi)
-p (protozoa)
Dependencies
ReferenceSeeker needs the following dependencies:
- Python (3.5.2), Biopython (1.71)
- Mash (2.2) https://github.com/marbl/Mash
- MUMmer (4.0.0-beta2) https://github.com/gmarcais/mummer
ReferenceSeeker has been tested against aforementioned versions.
Citation
ReferenceSeeker: rapid determination of appropriate reference genomes. Oliver Schwengers, Torsten Hain, Trinad Chakraborty, Alexander Goesmann. bioRxiv 863621; doi: https://doi.org/10.1101/863621
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