Introduction

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 repository.

If you use Kraken in your research, please cite the Kraken paper. Thank you!

System Requirements

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 k-mers.

  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 install the Jellyfish k-mer counter. Note that Kraken only supports use of Jellyfish version 1. Jellyfish version 2 is not yet compatible with Kraken.

• 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.