The proposed solution allows mapping sequencing reads to a reference genome. We deployed it on our own architecture based on the serverless computing service (named Lambda) provided by Amazon Web Service (AWS). The serverless environment was configured as follows:
- Ephemeral storage: 512 MB (maximum is 512 MB);
- Memory: 3,008 MB;
- Virtual CPUs (vCPUs): 2.
Note that more information will be provided on reasonable request.
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lambda_architecture.pdf : it is the architecture that our solution needs for working.
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lambda_function.py : it is a non-exhaustive adaptation of the lambda function for testing purpose only. The paths for a generic sample are already defined in the function, so you don't have to configure a trigger to test this function.
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results.xlsx : it is the results produced during experimentation.
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output_sample1_lambda.txt : an output produced by the proposed solution on a random sample.
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output_sample1_local.txt : an output produced by the a loval workstation the same sample used for output_sample1_lambda.txt .