Biomedical Chemistry: Research and Methods 2020, 4(4), e00131

Processing Oxford Nanopore Long Reads Using Amazon Web Services

V.V. Shapovalova1, S.P. Radko 2, K.G. Ptitsyn K.G.2, G.S. Krasnov2, K.V Nakhod2*, O.S Konash2, M.A. Vinogradina2,
E. A. Ponomarenko2, D. S. Druzhilovskiy2, A. V. Lisitsa 2,3

1Center for Strategic Planning and Management of Medical and Biological Health Risks,
10 bldg 1 Pogodinskaya str., Moscow, 119121 Russia
2Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia; *e-mail:
3West Siberian Interregional Scientific and Educational Center, Tyumen State University,
6 Volodarsky str., Tyumen, 625003 Russia

Keywords:postgenomic technologies, transcript; RNA, sequencing; bioinformatics; cloud computing


The whole version of this paper is available in Russian.

Studies of genomes and transcriptomes are performed using sequencers that read the sequence of nucleotide residues of genomic DNA, RNA, or complementary DNA (cDNA). The analysis consists of an experimental part (obtaining primary data) and bioinformatic processing of primary data. The bioinformatics part is performed with different sets of input parameters. The selection of the optimal values of the parameters, as a rule, requires significant computing power. The article describes a protocol for processing transcriptome data by virtual computers provided by the cloud platform Amazon Web Services (AWS) using the example of the recently emerging technology of long DNA and RNA sequences (Oxford Nanopore Technology). As a result, a virtual machine and instructions for its use have been developed, thus allowing a wide range of molecular biologists to independently process the results obtained using the "Oxford nanopore".

Figure 1. The fragments of working windows screenshots.
(a) MrFirst virtual machine (ONT) has the status of "running", which provides the possibility of remote connection. The configuration of the t2.micro virtual machine is shown in the "Instance Type" column. The connection to the virtual machine requires an IP address, which can be obtained by going to [Connect] in the [Actions] menu (see right).
(b) The connecting to the console using the PuTTу.
(c) The accessing the file system using the WinSCP. Detailed information (step-by-step instructions) can be found in the supplementary materials (Appendix 1).
Figure 2. The heat map showing the number of gigabases read in the MinION sequencer nanopore channels: (a) most cells are working and (b) the efficiency of half of the cells has significantly decreased. Each channel is marked with a "square" in the figure, the axes set the coordinates of the cell topology. The color depends on the amount of data read. Squares of white color mean that the cell did not work (for example, due to a technical error in the preparation of the experiment). Dark blue squares indicate that although information was coming from the cell, but the amount of data read in that cell was insignificant. Q>7 is a quality criterion for the sequencing process, reflecting that the number of working pores in the cell must be at least 7 times higher than the number of inactive pores.
Figure 3. The loading of data about the quantitative content of protein-coding gene transcripts in a biosample from quant.sf file to Microsoft Excel spreadsheet.

Table 1. The configuration parameters of virtual machines to process data obtained using ONT. vCPU - virtual CPU, GPU - NVidia graphic processor unit.

Table 2. The computing time required to process the results of human transcriptome analysis using nanopore ONT sequencing technology on Amazon Web Services.

Table 3. The size of raw data files and files with result of processing. Estimation time of downloading the results from the AWS server.


This work was supported by the Program of Fundamental Scientific Research of State Academies of Sciences for 2013-2020.


Supplementary materials are available at


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