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NGSANE: a lightweight production informatics framework for high-throughput data analysis

Authors: Buske, FA; French, HJ; Smith, MA; Clark, SJ; Bauer, DC;

NGSANE: a lightweight production informatics framework for high-throughput data analysis

Abstract

AbstractSummary: The initial steps in the analysis of next-generation sequencing data can be automated by way of software ‘pipelines’. However, individual components depreciate rapidly because of the evolving technology and analysis methods, often rendering entire versions of production informatics pipelines obsolete. Constructing pipelines from Linux bash commands enables the use of hot swappable modular components as opposed to the more rigid program call wrapping by higher level languages, as implemented in comparable published pipelining systems.Here we present Next Generation Sequencing ANalysis for Enterprises (NGSANE), a Linux-based, high-performance-computing-enabled framework that minimizes overhead for set up and processing of new projects, yet maintains full flexibility of custom scripting when processing raw sequence data.Availability and implementation: Ngsane is implemented in bash and publicly available under BSD (3-Clause) licence via GitHub at https://github.com/BauerLab/ngsane.Contact: Denis.Bauer@csiro.auSupplementary information: Supplementary data are available at Bioinformatics online.

Keywords

570, anzsrc-for: 46 Information and Computing Sciences, anzsrc-for: 49 Mathematical sciences, Laboratory, 3102 Bioinformatics and Computational Biology, Automation, 46 Information and Computing Sciences, Humans, 4601 Applied Computing, anzsrc-for: 31 Biological Sciences, Automation, Laboratory, anzsrc-for: 01 Mathematical Sciences, anzsrc-for: 4601 Applied Computing, High-Throughput Nucleotide Sequencing, Applications Notes, 004, Networking and Information Technology R&D (NITRD), anzsrc-for: 06 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 08 Information and Computing Sciences, Software, 31 Biological Sciences

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Top 10%
Green
gold