Difference between revisions of "Main Page/Featured article of the week/2016"
Shawndouglas (talk | contribs) (Added last week's article of the week.) |
Shawndouglas (talk | contribs) (Added the previous article of the week. Next article of the week will be two weeks later due to attack on wiki (downtime).) |
||
Line 17: | Line 17: | ||
<!-- Below this line begin pasting previous news --> | <!-- Below this line begin pasting previous news --> | ||
<h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: January 18–24:</h2> | <h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: January 25–31:</h2> | ||
<div style="padding:0.4em 1em 0.3em 1em;"> | |||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Reid BMCInformatics2014 15.jpg|220px]]</div> | |||
'''"[[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]]"''' | |||
Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. | |||
To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. | |||
By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples. ('''[[Journal:Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline|Full article...]]''')<br /> | |||
</div> | |||
|- | |||
|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: January 18–24:</h2> | |||
<div style="padding:0.4em 1em 0.3em 1em;"> | <div style="padding:0.4em 1em 0.3em 1em;"> | ||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 GroganzOpenSourceBR2011 Aug.png|220px]]</div> | <div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 GroganzOpenSourceBR2011 Aug.png|220px]]</div> |
Revision as of 18:10, 15 February 2016
If you're looking for the 2014 archive, it can be found here. The 2015 archive is here. |
Featured article of the week archive - 2016
Welcome to the LIMSwiki 2016 archive for the Featured Article of the Week.
Featured article of the week: January 25–31:Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples. (Full article...)
|