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. Researchers at division for bioinformatics, biocenter, Innsbruck Medical University, Innsbruck, Austria, developed 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 .
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