Amazon ec2 instance startup time6/24/2023 Basecalling Oxford Nanopore data is computationally intensive and requires GPUs. Real-time sequencing reduces the turnaround time in clinical applications.īasecalling is the conversion of the raw electrical signal generated by the sequencer, stored in FAST5 files, into character-based sequences and associated metadata (for example sample identifier and sequences quality) stored in the standard FASTQ format. Detecting methylation requires additional sequencing on other platforms. Methylation is a biochemical modification within the DNA that turns genes on or off. Longer reads allow for characterization of relevant genetic features relatively inaccessible for short-read technologies (such as structural variants). Oxford Nanopore offers various benefits compared to other sequencing technologies such as much longer read lengths (up to hundreds of kilobases), extracting information on methylation status, and real-time sequencing. In recent years significant technological advancements in Oxford Nanopore’s sequencers have made them a viable tool for sequencing DNA and RNA molecules. Our cost evaluations revealed that the g5.xlarge instance delivers the lowest cost for basecalling a whole human genome (WHG) with the Guppy tool. The Dorado basecaller outperformed Guppy by a factor of 3.8 x when performing methylation calling with the 5-hydroxymethylcytosine group (5hmCG). For example, at a rate of 400 bases per second (bps) passing through the nanopore, the sampling rate is 4,000 samples per second. Typically, the current signal is sampled at 10 times the speed at which the bases passing through the nanopore. ![]() A sample is one measurement of the current flowing through the nanopore. The top performance was achieved on a p4d.24xlarge instance type which delivered 490 million samples/second with Dorado, and 250 million samples/second with Guppy. We ran Guppy and Dorado on 20 different Amazon Elastic Compute Cloud (Amazon EC2) instance types with GPU accelerators. This benchmarking project was conducted in collaboration between G42 Healthcare, Oxford Nanopore Technologies and AWS. This blog post presents the benchmarking results for two of those Oxford Nanopore basecallers - Guppy and Dorado - on AWS. The resulting signal is decoded to provide the specific DNA or RNA sequence by virtue of compute-intensive algorithms called basecallers. They work by monitoring changes to an electrical current as nucleic acids are passed through a protein nanopore. ![]() Oxford Nanopore sequencers enables direct, real-time analysis of long DNA or RNA fragments. This blog post was contributed by Guilherme Coppini, Bioinformatician and Javier Quilez, Associate Director – Bioinformatics at G42 Healthcare and Chris Seymour, Vice President of Advanced Platform Development at Oxford Nanopore and Doruk Ozturk, Senior Solutions Architect, Container Technologies, and Michael Mueller, Senior Solutions Architect, Genomics at AWS and Stefan Dittforth, Senior Solutions Architect, Healthcare at AWS.
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