Functions extending the scons build tool for reproducible research in bioinformatics.
Project description
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 git@github.com: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
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