Its also easy to "encourage" people to help with the process, if you want to download from the main repository, you have to work for it. This will encourage universities to setup a server with a mirror. The NCBI can keep track of who is helping a lot and who is just leeching the system, leechers are put on a low priority. You could even spur companies that could charge for passwords to their mirrors...
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There's always "petabyte sneakernet" : http://www.codinghorror.com/blog/200...bandwidth.html
Maybe the Netflix model of a few years ago is the answer; instead of DVDs in the mail, computer cases with 8 bays of 3TB drives using "high bandwidth" Fedex trucks.
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As previously mentioned, torrents are as good as the number of sites willing to seed. NGS crowd is not that big yet. But if you use seqanswers as a measure of how fast it grows - torrent may become a feasible option in the future. Add to that universities, hospitals, federal agencies other then NIH who are beginnig to wake up to archival of NGS - they do have enough resources to seed the data.
Fedex solution while making a good joke is impractical. This argument is second only to "use fridge instead of NetApp".
And about compression. Look at compression not as a general "gzip fastq", but what real information do you really store. In resequencing ~90% of raw sequences perfectly match the reference. In functional sequencing you frequently end up with highly repetitive reads. Do you really care about pixel coordinates of every read? Do you really trust machine quality scores or recalibration approach is more then sufficient? etc...
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Its just a matter of implementing a system where you give a higher priority to people that help distribute the files, that should be enough to get a wide base of nodes. Regarding compression, it will only get you so far. Think of a world in which sequencing a chromatin mark or a TF is $100, beware big data is comming...
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Many torrents (especially "Pirate Bay"-style) do prioritize distributors over downloaders. This is not a technical problem.
Total cost of sequencing needs to include not only reagents, but sample collection and preparation, lab technician time, reproducibility of a sample, time to repeat experiment, etc. When this cost will be low enough to make archival economically senseless, it will stop. Compare it to "blood work": if physician doesn't believe in red cell counts, it is much cheaper to redo the test than to figure out what went wrong.
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Originally posted by srasdk View PostIn resequencing ~90% of raw sequences perfectly match the reference.
Originally posted by srasdk View PostWhen this cost will be low enough to make archival economically senseless, it will stop.
Thanks.
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1. The observation is general and not precise. It was done while working with the recent 1000 Genomes data. Sorry - the statement was too broad. Homo sapiens is a very inbred species and any personal germline genome is very close to the reference. Somatic changes (cancer) are more unpredictable. If you are interested in in biological diversity other then human, then you were right in confronting the statement, but currently NGS data production is heavily tilted toward human.
2. Before NGS phylogenetic studies were submitted as final and annotated sequences to GenBank. When community becomes confident that it can extract most of the information from raw data, there will be no point of archiving intermediate results.
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Innovations in next-generation sequencing technologies and techniques are driving more precise and comprehensive exploration of complex biological systems. Current advancements include improved accessibility for long-read sequencing and significant progress in single-cell and 3D genomics. This article explores some of the most impactful developments in the field over the past year.
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