This work was also supported by the NIAID/NIH grant HHSN272201400008C to RAMF. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All data files are available from the ENA database (project accession number(s) PRJEB9846, PRJEB12582, PRJEB9687).įunding: This work was supported by the European Union’s Horizon 2020 research and innovation program under grant agreements No 643476 (COMPARE), and No 653316 (EVAg). Received: JanuAccepted: DecemPublished: February 20, 2020Ĭopyright: © 2020 Poen et al. PLoS ONE 15(2):Įditor: Ming Zhang, University of Georgia, UNITED STATES (2020) Comparison of sequencing methods and data processing pipelines for whole genome sequencing and minority single nucleotide variant (mSNV) analysis during an influenza A/H5N8 outbreak. Nevertheless, minority variant analysis will need a different level of careful standardization and awareness about the possible limitations, as shown in this study.Ĭitation: Poen MJ, Pohlmann A, Amid C, Bestebroer TM, Brookes SM, Brown IH, et al. However, homopolymer errors aside, there was generally a good agreement between consensus sequences that were obtained for all combinations of sequencing platforms and data processing pipelines.

This analysis demonstrated that variation in the final result could be attributed to all stages in the process, but the most critical were the well-known homopolymer errors introduced by 454 sequencing, and the alignment processes in the different data processing pipelines which affected the consistency of mSNV detection. In order to determine the comparability of consensus sequences and minority (sub-consensus) single nucleotide variant (mSNV) identification, the biological samples, the sequence data from 3 sequencing platforms and the *.bam quality-trimmed alignment files of raw data of 3 influenza A/H5N8 viruses were shared.

This manuscript describes the next-generation sequencing of three closely related viruses, each analysed using different sequencing strategies, sequencing instruments and data processing pipelines. Conversely, understanding where agreement cannot be achieved provides insight into the limitations of these approaches and also allows efforts to be focused on areas of the process that need improvement. As high-throughput sequencing technologies are becoming more widely adopted for analysing pathogens in disease outbreaks there needs to be assurance that the different sequencing technologies and approaches to data analysis will yield reliable and comparable results.

Change nuclotide contig in bioedit