Skip to content


Switch branches/tags


Failed to load latest commit information.
Latest commit message
Commit time
Jul 13, 2019



Jellyfish is a tool for fast, memory-efficient counting of k-mers in DNA. A k-mer is a substring of length k, and counting the occurrences of all such substrings is a central step in many analyses of DNA sequence. Jellyfish can count k-mers using an order of magnitude less memory and an order of magnitude faster than other k-mer counting packages by using an efficient encoding of a hash table and by exploiting the "compare-and-swap" CPU instruction to increase parallelism.

JELLYFISH is a command-line program that reads FASTA and multi-FASTA files containing DNA sequences. It outputs its k-mer counts in a binary format, which can be translated into a human-readable text format using the "jellyfish dump" command, or queried for specific k-mers with "jellyfish query". See the documentation for details.

If you use Jellyfish in your research, please cite:

Guillaume Marcais and Carl Kingsford, A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics (2011) 27(6): 764-770 (first published online January 7, 2011) doi:10.1093/bioinformatics/btr011


Linux Binaries

On Debian and Ubuntu with apt:

sudo apt update
sudo apt install jellyfish

On Arch, it is available from AUR.


Jellyfish can be installed on FreeBSD via the FreeBSD ports system.

To install via the binary package, simply run:

pkg install Jellyfish

To install from source:

cd /usr/ports/biology/jellyfish
make install


With Cygwin, Jellyfish can be compiled from source as explained below. The simpler way on Windows 10 is to first install WSL and then install a Linux distribution that carries Jellyfish (e.g., Ubuntu) from the Windows Store. Finally, install with:

sudo apt update
sudo apt install jellyfish

From source

To get an easier to compiled packaged tar ball of the source code, download a release from the github release. You need make and g++ version 4.4 or higher. To install in your home directory, do:

./configure --prefix=$HOME
make -j 4
make install

To compile from the git tree, you will also need autoconf, automake, libool, gettext, pkg-config and yaggo. Then to compile and install (in /usr/local in that example) with:

autoreconf -i
make -j 4
sudo make install

If the software is installed in system directories (hint: you needed to use sudo to install), like the example above, then the system library cache must be updated like such:

sudo ldconfig


Instruction of use are available in the doc directory.

Extra / Examples

In the examples directory are potentially useful extra programs to query/manipulates output files of Jellyfish, using the shared library of Jellyfish in C++ or with scripting languages. The examples are not compiled by default. Each subdirectory of examples is independent and is compiled with a simple invocation of 'make'.

Binding to script languages

Bindings to Ruby, Python and Perl are provided. This binding allows to read the output file of Jellyfish directly in a scripting language. Compilation of the bindings is easier from the release tarball. The development files of the target scripting language are required.

Compilation of the bindings from the git tree requires SWIG version 3 and adding the switch --enable-swig to the configure command lines show below.

To compile all three bindings, configure and compile with:

./configure --enable-ruby-binding --enable-python-binding --enable-perl-binding
make -j 4
sudo make install

By default, Jellyfish is installed in /usr/local and the bindings are installed in the proper system location. When the --prefix switch is passed, the bindings are installed in the given directory. For example:

./configure --prefix=$HOME --enable-python-binding
make -j 4
make install

This will install the python binding in $HOME/lib/python2.7/site-packages (adjust based on your Python version).

Then, for Python, Ruby or Perl to find the binding, an environment variable may need to be adjusted (PYTHONPATH, RUBYLIB and PERL5LIB respectively). For example:

export PYTHONPATH=$HOME/lib/python2.7/site-packages

See the swig directory for examples on how to use the bindings.