Single Particle Data Analysis Suite
Arachnid is an open source software package written primarily in Python that processes images of macromolecules captured by cryo-electron microscopy (cryo-EM). Arachnid is focused on automating the single-particle reconstruction workflow and can be thought of as two subpackages:
- Arachnid Prime
- A SciPy Toolkit (SciKit) that focuses on every step of the single-particle reconstruction workflow up to orientation assignment and classification. This toolkit also includes a set of application scripts and a workflow manager.
- This subpackage functions as an interface to the SPIDER package. It includes both a library of SPIDER commands and a set of application scripts to run a set of procedures for every step of single-particle reconstruction including orientation assignment but not classification.
Arachnid Prime currently focuses on automating the pre-processing of the image data captured by cryo-EM. For example, Arachnid has the following highlighted applications handle the particle-picking problem:
- AutoPicker: Automated reference-free particle selection
- ViCer: Automated unsupervised particle verification
For more information, see http://www.arachnid.us.
Alternatively, HTML documentation can be built locally using
python setup.py build_sphinx, which assumes you have the prerequisite
Python libraries. The documents can be found in
How to cite
The main reference to cite is:
Langlois, R. E., Ho D. N., Frank, J., 2014. Arachnid: Automated Image-processing for Electron Microscopy. In Preparation.
See CITE for more information and downloadable citations.
The required dependencies to build the software are Python >= 2.6, setuptools, Numpy >= 1.3, SciPy >= 0.7, matplotlib>=1.1.0, mpi4py>=1.2.2, scikit-learn, scikit-image, psutil, sqlalchemy, mysql-python, PIL, basemap, FFTW3 or MKL, and both C/C++ and Fortran compilers.
It is also recommended you install NumPy and SciPy with an optimized Blas library such as MKL, ACML, ATLAS or GOTOBlas.
To build the documentation, Sphinx>=1.0.4 is required.
All of these dependencies can be found in a single free binary package: Anaconda.
The prefered method of installation is to use Anaconda:
# If you do not have Anaconda then run the following (assumes bash shell) wget http://repo.continuum.io/miniconda/Miniconda-3.0.0-Linux-x86_64.sh sh Miniconda-3.0.0-Linux-x86_64.sh -b -p $PWD/anaconda export PATH=$PWD/anaconda/bin:$PATH # If you have anaconda or just installed it, then run conda install -c https://conda.binstar.org/ezralanglois arachnid
# Install from downloaded source
$ python setup.py install –prefix=$HOME
# Using Setup tools
$ easy_install arachnid
# Using PIP
$ pip install arachnid
# Using Anaconda
$ conda install -c https://conda.binstar.org/ezralanglois arachnid
You can check out the latest source with the command:
git clone https://github.com/ezralanglois/arachnid/arachnid.git