Treffer: Bioinformatic pipelines in Python with Leaf.

Title:
Bioinformatic pipelines in Python with Leaf.
Authors:
Napolitano F; Department of Computer Science (DI),University of Salerno, Fisciano (SA) 84084, Italy. fnapolitano@unisa.it, Mariani-Costantini R, Tagliaferri R
Source:
BMC bioinformatics [BMC Bioinformatics] 2013 Jun 21; Vol. 14, pp. 201. Date of Electronic Publication: 2013 Jun 21.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: [London] : BioMed Central, 2000-
MeSH Terms:
Software*, Computational Biology/*methods, DNA Copy Number Variations
References:
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Entry Date(s):
Date Created: 20130622 Date Completed: 20140206 Latest Revision: 20211021
Update Code:
20250114
PubMed Central ID:
PMC3747863
DOI:
10.1186/1471-2105-14-201
PMID:
23786315
Database:
MEDLINE

Weitere Informationen

Background: An incremental, loosely planned development approach is often used in bioinformatic studies when dealing with custom data analysis in a rapidly changing environment. Unfortunately, the lack of a rigorous software structuring can undermine the maintainability, communicability and replicability of the process. To ameliorate this problem we propose the Leaf system, the aim of which is to seamlessly introduce the pipeline formality on top of a dynamical development process with minimum overhead for the programmer, thus providing a simple layer of software structuring.
Results: Leaf includes a formal language for the definition of pipelines with code that can be transparently inserted into the user's Python code. Its syntax is designed to visually highlight dependencies in the pipeline structure it defines. While encouraging the developer to think in terms of bioinformatic pipelines, Leaf supports a number of automated features including data and session persistence, consistency checks between steps of the analysis, processing optimization and publication of the analytic protocol in the form of a hypertext.
Conclusions: Leaf offers a powerful balance between plan-driven and change-driven development environments in the design, management and communication of bioinformatic pipelines. Its unique features make it a valuable alternative to other related tools.