We plan to put fastq files generated in several RNA seq projects into long term storage using a local service. Because we are working with hundreds of fastq files, we are trying to determine the best method to store the files. The choice is between grouping all of the files into one giant tarball for storage or to break up the fastq files into individual project. One is easier to store, one is easier to access later (for meta-analyses?). Does anyone have any idea whether it makes sense to spend the extra effort to organize the files now?
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Trying to recover some specific piece of data would be a nightmare if you make one giant tarball; depending on the overall size, it's faster, cheaper and probably just as useful to simply delete all the data, rather than sending it to long-term storage in a disorganized mess.
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I would break it based on project and with a simple read me file with each folder to describe whats in each folder.Originally posted by Drerio View PostWe plan to put fastq files generated in several RNA seq projects into long term storage using a local service. Because we are working with hundreds of fastq files, we are trying to determine the best method to store the files. The choice is between grouping all of the files into one giant tarball for storage or to break up the fastq files into individual project. One is easier to store, one is easier to access later (for meta-analyses?). Does anyone have any idea whether it makes sense to spend the extra effort to organize the files now?
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by SEQadmin2
Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.
We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing...-
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