The high-throughput DNA sequencing equipments produce huge volumes of data with an ever increasing rate. While the sequencing cost drops by ≈5x per year, the cost of computing at best reduces by ≈2x. Very soon, interpreting the omics data will cost a lot more than generating it.
Cloud computing services dedicated to bioinformatics seems promising to keep pace with that massive sequencing data generation. Thus, nowadays we hear a lot on cloud computing services providing speedy sequence analysis.
Despite the difficulties of processing sequencing data due to its volume and structure, the initial problem is to transmit the data from where it is produced to where it will be processed.
Typically, this is uploading the DNA sequencing data from a life science center to a remote cloud computing environment.
In such a scenario, using the regular courier services will not be sustainable due to many problems they mainly introduce stemming from the size of the data to be transmitted in practice such as privacy, tracing, accountability, and etc. Thus, the data needs to flow from digital lines. Notice that the size of the data to flow from the transmission lines will be so huge that, even in case of leased lines or direct connections, the importance of transmission is not expected to diminish.
Proposing an efficient solution for that problem requires deep understanding of the needs in the life science side, and also the capabilities on the computing side. Since doing something to better compress the data is not the ultimate goal, but reducing the response time is, the whole operation from transmission to the end of processing should be considered simultaneously with an industry perspective rather than a pure computer science research opinion.
An interesting gap appears at this point. Life sciences people are busy with perfecting their data generation, and similarly cloud service providers focus on speeding up their processing pipeline, but the transmission of data becomes orphan and not considered seriously.
The classical way of massive data transmission is the compress – transmit – decompress scheme. However, compression/decompression of sequencing data is not an easy task due to its structure and massive size. Sometimes it takes more time and resources than required to analyze the genomic data itself. More, the resources spent on compression does not help much in further steps of analysis, and in some sense, the effort deployed on efficient transmission actually becomes wasted at the end.
Interestingly, some DNA sequencing centers submit their data to the cloud service providers on a hard that is carried by a regular courier service such as FedEx, or UPS. Surely, such a transmission is not sustainable with the increasing number of sequencing centers.
The recent shining results in the genomics area will revolutionize the medicine. Personalized medicine is coming closer than ever. In the very near future, sequencing will become a regular diagnosis tool, where not only the research centers but almost all health institutions will begin generating data. Not surprisingly, getting engaged with dedicated cloud services will be the choice of those institutions, which does not prefer to deal with the hassle of computing infrastructure.
They will surely seek for the best service that provides shortest response time, which is not the time elapsed in the cloud computing side, but the total time elapsed between the beginning of the transmission and the receipt of the final result. Thus, transmitting the data in an efficient way will become more important in that sense.
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