Difference between revisions of "Template:Article of the week"

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(Updated article of the week text.)
(Updated article of the week text.)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 SinghBMCBioinformatics2015 12-6.png|220px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 OConnor BMCInformatics2010 11-12.jpg|240px]]</div>
'''"[[Journal:SaDA: From sampling to data analysis—An extensible open source infrastructure for rapid, robust and automated management and analysis of modern ecological high-throughput microarray data|SaDA: From sampling to data analysis—An extensible open source infrastructure for rapid, robust and automated management and analysis of modern ecological high-throughput microarray data]]"'''
'''"[[Journal:SeqWare Query Engine: Storing and searching sequence data in the cloud|SeqWare Query Engine: Storing and searching sequence data in the cloud]]"'''


One of the most crucial characteristics of day-to-day [[laboratory]] information management is the collection, storage and retrieval of [[information]] about research subjects and environmental or biomedical samples. An efficient link between sample data and experimental results is absolutely important for the successful outcome of a collaborative project. Currently available software solutions are largely limited to large scale, expensive commercial [[Laboratory information management system|Laboratory Information Management Systems]] (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but most of the times this requires a sufficient investment of money, time and technical efforts. There is a clear need for a light weighted open source system which can easily be managed on local servers and handled by individual researchers. Here we present a software named SaDA for storing, retrieving and analyzing data originated from microorganism monitoring experiments. SaDA is fully integrated in the management of environmental samples, oligonucleotide sequences, microarray data and the subsequent downstream analysis procedures. It is simple and generic software, and can be extended and customized for various environmental and biomedical studies. ('''[[Journal:SaDA: From sampling to data analysis—An extensible open source infrastructure for rapid, robust and automated management and analysis of modern ecological high-throughput microarray data|Full article...]]''')<br />
Since the introduction of next-generation DNA sequencers the rapid increase in [[Sequencing|sequencer]] throughput, and associated drop in costs, has resulted in more than a dozen human [[Genomics|genomes]] being resequenced over the last few years. These efforts are merely a prelude for a future in which genome resequencing will be commonplace for both biomedical research and clinical applications. The dramatic increase in sequencer output strains all facets of computational infrastructure, especially databases and query interfaces. The advent of cloud computing, and a variety of powerful tools designed to process petascale datasets, provide a compelling solution to these ever increasing demands.
 
In this work, we present the [[SeqWare]] Query Engine which has been created using modern cloud computing technologies and designed to support databasing information from thousands of genomes. Our backend implementation was built using the highly scalable, NoSQL HBase database from the Hadoop project. We also created a web-based frontend that provides both a programmatic and interactive query interface and integrates with widely used genome browsers and tools. ('''[[Journal:SeqWare Query Engine: Storing and searching sequence data in the cloud|Full article...]]''')<br />


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''Recently featured'': [[Journal:Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline|Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline]], [[Journal:Benefits of the community for partners of open source vendors|Benefits of the community for partners of open source vendors]], [[Journal:adLIMS: A customized open source software that allows bridging clinical and basic molecular research studies|adLIMS: A customized open source software that allows bridging clinical and basic molecular research studies]]
''Recently featured'': [[Journal:SaDA: From sampling to data analysis—An extensible open source infrastructure for rapid, robust and automated management and analysis of modern ecological high-throughput microarray data|SaDA: From sampling to data analysis—An extensible open source infrastructure for rapid, robust and automated management and analysis of modern ecological high-throughput microarray data]], [[Journal:Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline|Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline]], [[Journal:Benefits of the community for partners of open source vendors|Benefits of the community for partners of open source vendors]]

Revision as of 17:04, 22 February 2016

Fig1 OConnor BMCInformatics2010 11-12.jpg

"SeqWare Query Engine: Storing and searching sequence data in the cloud"

Since the introduction of next-generation DNA sequencers the rapid increase in sequencer throughput, and associated drop in costs, has resulted in more than a dozen human genomes being resequenced over the last few years. These efforts are merely a prelude for a future in which genome resequencing will be commonplace for both biomedical research and clinical applications. The dramatic increase in sequencer output strains all facets of computational infrastructure, especially databases and query interfaces. The advent of cloud computing, and a variety of powerful tools designed to process petascale datasets, provide a compelling solution to these ever increasing demands.

In this work, we present the SeqWare Query Engine which has been created using modern cloud computing technologies and designed to support databasing information from thousands of genomes. Our backend implementation was built using the highly scalable, NoSQL HBase database from the Hadoop project. We also created a web-based frontend that provides both a programmatic and interactive query interface and integrates with widely used genome browsers and tools. (Full article...)


Recently featured: SaDA: From sampling to data analysis—An extensible open source infrastructure for rapid, robust and automated management and analysis of modern ecological high-throughput microarray data, Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline, Benefits of the community for partners of open source vendors

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