bioscons 0.8.1

This package extends the scons build tool for the construction of reproducible workflows in bioinformatics.

This project is in fairly early stages of development, although it is being used fairly heavily by the developers to support both research and clinical computational pipelines.

Background

Why does SCons make sense for reproducible bioinformatics pipelines?

• SCons has a sophisticated mechanism for determining dependencies, meaning that re-running SCons will only re-execute steps needing updating
• Most of the work of pipelines is done by external programs, and SCons is explicitly designed to make it easy to run external programs
• On the other hand, SCons also allows the execution of arbitrary python code in creating your script, and thus one can leverage the power of the python standard library, Biopython, NumPy, etc in your script.
• Rather than dealing with a mess of filenames, subsequent steps in an SCons build are expressed in terms of file objects
• Steps in the pipeline are implemented as Commands which implement a shell command or a python function in a in a way that consistently channels inputs into outputs
• Provides multiple mechanisms for cleanly executing isolated steps of the workflow
• SCons validates files and can fail incrementally

Alternative tools

make

Make is a classic and everywhere, but getting make to do complex things requires specialized (and often opaque) syntax

ruffus

ruffus is a lightweight way to automate bioinformatics pipelines. It also supports incremental recalculation. It does not, however, provide assistance for executing shell commands or managing files, and these must be done with explict sytem calls on “hand-built” strings.

galaxy

galaxy is a web-based tool for building remotely-executed workflows. This is a hugely attractive framework for exposing complex workflows using a graphical-interface, but occupies a very different niche from this project (which provides a command line interface to locally-executed programs).

Documentation

Documentation is available on github: http://nhoffman.github.io/bioscons/

Installation

dependencies

• bioscons requires scons 2.x

installation from PyPi

Installation is simplest using pip:

pip install bioscons

installation from source

Obtain the source code from github. For read-only access:

git clone git://github.com/nhoffman/bioscons.git

For committers:

git clone [e-mail]:nhoffman/bioscons.git

Then install:

cd bioscons
python setup.py install

For developers, a virtualenv containing all dependencies can be created using a script:

cd bioscons
dev/mkvenv.sh