A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines.

ABSTRACT:

Background

Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts.

Results

To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes

SUBMITTER: Cieslik M 

PROVIDER: S-EPMC3051902 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature