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In the case of the Autogene alignment algorithm, we wrote a client script that communicates with the cloud backend, running two tiers of algorithms that splits up the job into many subjobs running in parallel. We have tested this on an alignment of the PUC18 gene, which consists of a sequence of 2,680 letters, against a library of 17,498 yeast features, each about 400 base-pairs long. Running conventionally without the cloud, we found that it would take about 39 minutes to complete this alignment. Running it on the cloud with 10 processors we cut the time to three minutes, and running it with 30 processors we cut it to nearly one minute. PUC18 is a relatively unintimidating-sized sequence. Considering how many sequences of interest can be up to thousands of letters in length, and how libraries can have countless features, which could cause alignments to take weeks to complete, certain alignment tasks would require more memory than a local machine would be able to handle, so this is the kind of job that could only be done through a cloud server. With this kind of improvement, we are making the impossible in biology possible. |
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