Kraken is a taxonomic sequence
classifier that assigns taxonomic labels to short DNA reads. It does
this by examining the k-mers within a read and querying a
database with those k-mers. This database contains a mapping of
every k-mer in
Kraken's genomic library to
the lowest common ancestor (LCA) in a taxonomic tree of all genomes that
contain that k-mer. The set of LCA taxa that correspond to the
k-mers in a read are then analyzed to create a single taxonomic
label for the read; this label can be any of the nodes in the taxonomic
tree. Kraken is designed to be
rapid, sensitive, and highly precise. Our tests on various real and
simulated data have shown
Kraken to have sensitivity
slightly lower than Megablast with precision being slightly higher. On a
set of simulated 100 bp reads,
Kraken processed over 1.3
million reads per minute on a single core in normal operation, and over
4.1 million reads per minute in quick operation.
The latest released version of Kraken will be available at the Kraken
website, and the latest updates
to the Kraken source code are available at the Kraken GitHub
If you use Kraken in your
research, please cite the Kraken
paper. Thank you!
Note: Users concerned about the disk or memory requirements should read
the paragraph about MiniKraken, below.
Disk space: Construction of Kraken's standard database will
require at least 160 GB of disk space. Customized databases may
require more or less space. Disk space used is linearly proportional
to the number of distinct k-mers; as of Feb. 2015, Kraken's
default database contains just under 6 billion (6e9) distinct
In addition, the disk used to store the database should be
locally-attached storage. Storing the database on a network
filesystem (NFS) partition can cause Kraken's operation to be very
slow, or to be stopped completely. As NFS accesses are much slower
than local disk accesses, both preloading and database building will
be slowed by use of NFS.
Memory: To run efficiently, Kraken requires enough free memory to
hold the database in RAM. While this can be accomplished using a
ramdisk, Kraken supplies a utility for loading the database into RAM
via the OS cache. The default database size is 75 GB (as of Feb.
2015), and so you will need at least that much RAM if you want to
build or run with the default database.
Dependencies: Kraken currently makes extensive use of Linux
utilities such as sed, find, and wget. Many scripts are written using
the Bash shell, and the main scripts are written using Perl. Core
programs needed to build the database and run the classifier are
written in C++, and need to be compiled using g++. Multithreading is
handled using OpenMP. Downloads of NCBI data are performed by wget
and in some cases, by rsync. Most Linux systems that have any sort of
development package installed will have all of the above listed
programs and libraries available.
Finally, if you want to build your own database, you will need to
k-mer counter. Note that Kraken only supports use of
Jellyfish version 1. Jellyfish version 2 is not yet compatible with
Network connectivity: Kraken's standard database build and
download commands expect unfettered FTP and rsync access to the NCBI
FTP server. If you're working behind a proxy, you may need to set
certain environment variables (such as ftp_proxy or
RSYNC_PROXY) in order to get these commands to work properly.
MiniKraken: To allow users with low-memory computing environments
to use Kraken, we supply a reduced standard database that can be
downloaded from the Kraken web site. When Kraken is run with a
reduced database, we call it MiniKraken.
The database we make available is only 4 GB in size, and should run
well on computers with as little as 8 GB of RAM. Disk space required
for this database is also only 4 GB.