SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments

David Burdick(Institute for Systems Biology), Christopher Cavnor(Seattle University), Jeremy Handcock(Seattle University), Sarah Killcoyne(Institute for Systems Biology), Jake Lin(Seattle University), Bruz Marzolf(Seattle University), Stephen A. Ramsey(Institute for Systems Biology), Hector Rovira(Seattle University), Ryan Bressler(Seattle University), Ilya Shmulevich(Institute for Systems Biology), John Boyle(Seattle University)
BMC Bioinformatics
July 14, 2010
Cited by 4Open Access
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Abstract

BACKGROUND: High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. RESULTS: Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. CONCLUSION: The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services.


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