Some script to download bacterial and fungal genomes from NCBI after they restructured their FTP a while ago.
Idea shamelessly stolen from Mick Watson's Kraken downloader
that can also be found in Mick's GitHub
repo. However, Mick's
written in Perl specific to actually building a Kraken database
So this is a set of scripts that focuses on the actual genome downloading.
pip install ncbi-genome-download
Alternatively, clone this repository from GitHub, then run (in a python virtual environment)
pip install .
If this fails on older versions of Python, try updating your
pip tool first:
pip install --upgrade pip
and then rerun the
ncbi-genome-download is packaged in
Refer the the Anaconda/miniconda site to install a distribution (highly recommended) https://conda.io/miniconda.html
With that installed one can do:
conda install -c bioconda ncbi-genome-download
ncbi-genome-download is only developed and tested on Python releases still under active
support by the Python project. At the moment, this means versions 3.5, 3.6, 3.7, and 3.8.
Specifically, no attempt at testing under Python versions older than 3.5 is being made.
If your system is stuck on an older version of Python, consider using a tool like Homebrew to obtain a more up-to-date version.
ncbi-genome-download 0.2.12 was the last version to support Python 2.
To download all bacterial RefSeq genomes in GenBank format from NCBI, run the following:
Downloading multiple groups is also possible:
Note: To see all available groups, see
ncbi-genome-download --help, or simply use
all to check all groups.
Naming a more specific group will reduce the download size and the time needed to find the sequences to download.
If you're on a reasonably fast connection, you might want to try running multiple downloads in parallel:
ncbi-genome-download bacteria --parallel 4
To download all fungal GenBank genomes from NCBI in GenBank format, run:
ncbi-genome-download --section genbank fungi
To download all viral RefSeq genomes in FASTA format, run:
ncbi-genome-download --formats fasta viral
It is possible to download multiple formats by supplying a list of formats or simply download all formats:
ncbi-genome-download --formats fasta,assembly-report viral ncbi-genome-download --formats all viral
To download only completed bacterial RefSeq genomes in GenBank format, run:
ncbi-genome-download --assembly-levels complete bacteria
It is possible to download multiple assembly levels at once by supplying a list:
ncbi-genome-download --assembly-levels complete,chromosome bacteria
To download only bacterial reference genomes from RefSeq in GenBank format, run:
ncbi-genome-download --refseq-categories reference bacteria
To download bacterial RefSeq genomes of the genus Streptomyces, run:
ncbi-genome-download --genera Streptomyces bacteria
Note: This is a simple string match on the organism name provided by NCBI only.
You can also use this with a slight trick to download genomes of a certain species as well:
ncbi-genome-download --genera "Streptomyces coelicolor" bacteria
Note: The quotes are important. Again, this is a simple string match on the organism name provided by the NCBI.
Multiple genera is also possible:
ncbi-genome-download --genera "Streptomyces coelicolor,Escherichia coli" bacteria
You can also put genus names into a file, one organism per line, e.g.:
Then, pass the path to that file (e.g.
my_genera.txt) to the
--genera option, like so:
ncbi-genome-download --genera my_genera.txt bacteria
Note: The above command will download all Streptomyces and Amycolatopsis genomes from RefSeq.
You can make the string match fuzzy using the
--fuzzy-genus option. This can be handy if you need to match
a value in the middle of the NCBI organism name, like so:
ncbi-genome-download --genera coelicolor --fuzzy-genus bacteria
Note: The above command will download all bacterial genomes containing "coelicolor" anywhere in their organism name from RefSeq.
To download bacterial RefSeq genomes based on their NCBI species taxonomy ID, run:
ncbi-genome-download --species-taxids 562 bacteria
Note: The above command will download all RefSeq genomes belonging to Escherichia coli.
To download a specific bacterial RefSeq genomes based on its NCBI taxonomy ID, run:
ncbi-genome-download --taxids 511145 bacteria
Note: The above command will download the RefSeq genome belonging to Escherichia coli str. K-12 substr. MG1655.
It is also possible to download multiple species taxids or taxids by supplying the numbers in a comma-separated list:
ncbi-genome-download --taxids 9606,9685 --assembly-level chromosome vertebrate_mammalian
Note: The above command will download the reference genomes for cat and human.
In addition, you can put multiple species taxids or taxids into a file, one per line
and pass that filename to the
--taxids parameters, respectively.
Assuming you had a file
my_taxids.txt with the following contents:
You could download the reference genomes for cat and human like this:
ncbi-genome-download --taxids my_taxids.txt --assembly-levels chromosome vertebrate_mammalian
It is possible to also create a human-readable directory structure in parallel to mirroring the layout used by NCBI:
ncbi-genome-download --human-readable bacteria
This will use links to point to the appropriate files in the NCBI directory structure, so it saves file space. Note that links are not supported on some Windows file systems and some older versions of Windows.
It is also possible to re-run a previous download with the
In this case,
ncbi-genome-download will not download any new genome files, and just create
human-readable directory structure. Note that if any files have been changed on the NCBI side,
a file download will be triggered.
There is a "dry-run" option to show which accessions would be downloaded, given your filters:
ncbi-genome-download --dry-run bacteria
If you want to filter for the "relation to type material" column of the
assembly summary file, you can use the
--type-materials option. Possible
values are "any", "all", "type", "reference", "synonym", "proxytype", and/or
"neotype". "any" will include assemblies with no relation to type material
value defined, "all" will download only assemblies with a defined value.
Multiple values can be given, separated by comma:
ncbi-genome-download --type-materials type,reference
By default, ncbi-genome-download caches the assembly summary files for the respective taxonomic
groups for one day. You can skip using the cache file by using the
The output of
--help also shows the cache directory, should you want to remove any of the cached
To get an overview of all options, run
You can also use it as a method call. Pass the pythonised keyword arguments (
_ instead of
as described above or in the
import ncbi_genome_download as ngd ngd.download()
Note: To specify a taxonomic group, like bacteria, use the
This script lets you find out what TaxIDs to pass to
ngd, and will write a simple one-item-per-line
file to pass in to it. It utilises the
ete3 toolkit, so refer to their site to install the dependency
if it's not already satisfied.
You can query the database using a particular TaxID, or a scientific name. The primary function of the script is to return all the child taxa of the specified parent taxa. The script has various options for what information is written in the output.
A basic invocation may look like:
# Fetch all descendent taxa for Escherichia (taxid 561): python gimme_taxa.py -o ~/mytaxafile.txt 561 # Alternatively, just provide the taxon name python gimme_taxa.py -o all_descendent_taxids.txt Escherichia # You can provide multiple taxids and/or names python gimme_taxa.py -o all_descendent_taxids.txt 561,Methanobrevibacter
On first use, a small sqlite database will be created in your home directory
by default (change the location with the
--database flag). You can update this database
by using the
--update flag. Note that if the database is not in your home directory,
you must specify it with
--database or a new database will be created in your home
To see all help:
python gimme_taxa.py python gimme_taxa.py -h python gimme_taxa.py --help
All code is available under the Apache License version 2, see the
LICENSE file for details.