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SIMPLEX: Cloud-Enabled Pipeline for the Comprehensive Analysis of Exome Sequencing Data

Overview of attention for article published in PLOS ONE, August 2012
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Title
SIMPLEX: Cloud-Enabled Pipeline for the Comprehensive Analysis of Exome Sequencing Data
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0041948
Pubmed ID
Authors

Maria Fischer, Rene Snajder, Stephan Pabinger, Andreas Dander, Anna Schossig, Johannes Zschocke, Zlatko Trajanoski, Gernot Stocker

Abstract

In recent studies, exome sequencing has proven to be a successful screening tool for the identification of candidate genes causing rare genetic diseases. Although underlying targeted sequencing methods are well established, necessary data handling and focused, structured analysis still remain demanding tasks. Here, we present a cloud-enabled autonomous analysis pipeline, which comprises the complete exome analysis workflow. The pipeline combines several in-house developed and published applications to perform the following steps: (a) initial quality control, (b) intelligent data filtering and pre-processing, (c) sequence alignment to a reference genome, (d) SNP and DIP detection, (e) functional annotation of variants using different approaches, and (f) detailed report generation during various stages of the workflow. The pipeline connects the selected analysis steps, exposes all available parameters for customized usage, performs required data handling, and distributes computationally expensive tasks either on a dedicated high-performance computing infrastructure or on the Amazon cloud environment (EC2). The presented application has already been used in several research projects including studies to elucidate the role of rare genetic diseases. The pipeline is continuously tested and is publicly available under the GPL as a VirtualBox or Cloud image at http://simplex.i-med.ac.at; additional supplementary data is provided at http://www.icbi.at/exome.

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Geographical breakdown

Country Count As %
United States 8 7%
United Kingdom 3 3%
France 2 2%
India 2 2%
Italy 1 <1%
Ghana 1 <1%
Austria 1 <1%
Switzerland 1 <1%
Netherlands 1 <1%
Other 3 3%
Unknown 90 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 32%
Student > Ph. D. Student 23 20%
Student > Master 12 11%
Professor > Associate Professor 11 10%
Student > Bachelor 8 7%
Other 16 14%
Unknown 7 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 50%
Computer Science 20 18%
Biochemistry, Genetics and Molecular Biology 11 10%
Engineering 7 6%
Medicine and Dentistry 6 5%
Other 2 2%
Unknown 11 10%