miCloud: a plug and play, on-premises bioinformatics cloud, providing seamless integration with Illumina genome sequencers
Baekdoo Kim, Thahmina A. AliiD, Konstantinos KrampisiD, Changsu Dong, Bobby P. LaunganiiD, Claudia WultschiD, Carlos Lijeron
Abstract
Benchtop genome sequencers such as the Illumina MiSeq or MiniSeq [1], [2] are revolutionizing genomics research for smaller, independent laboratories, by enabling access to low-cost Next Generation Sequencing (NGS) technology in-house. These benchtop genome sequencing instruments require only standard laboratory equipment, in addition to minimal time for sample preparation. However, post-sequencing bioinformatics data analysis still presents a significant bottleneck, for research laboratories lacking specialized software and technical data analysis skills on their teams. While bioinformatics computes clouds providing solutions following a Software as a Service (SaaS) are available ([3]-[6], review in [7]), currently, there are only a few options which are user-friendly for non-experts while at the same time are also low-cost or free. One primary example is Illumina BaseSpace [8] that is very easy to access by non-experts, and also offers an integrated solution where data are streamed directly from the MiSeq sequencing instrument to the cloud. Once the data is on the BaseSpace cloud, users can access a range of bioinformatics applications with pre-installed algorithms through an intuitive web interface. Nonetheless, BaseSpace can be a costly solution as a yearly subscription depending on whether the user is associated with an academic or private institution, ranges in price from $999 - $4,999. Additional \"iCredits\" [9] might need to be purchased for frequent users that exhaust the base credit allowance as part of the subscription. Considering the reduction of computer hardware cost in recent years, a multi-core Intel Xeon server with 64 GigaByte (GB) of memory and multiple TeraByte (TB) of storage is priced less than the yearly subscription to Basespace [10], and similarly when compared to renting compute cycles from providers such as Amazon Web Services (AWS) [11]. Furthermore, the current generation of laptops usually come with 6-10 GigaBytes (GB) of memory and 1 TeraByte (TB) of storage, providing enough computational capacity to analyze data from small NGS experiments [12] that include only a few samples.
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