Fig. 5

Metagenomic identification of EBOV from a clinical blood sample by nanopore sequencing and MetaPORE real-time bioinformatics analysis. Nanopore data generated from the Ebola2 library and sequenced on flow cell #3 were analyzed in real time using the MetaPORE bioinformatics analysis pipeline, and compared to corresponding Illumina MiSeq data. a Time line of nanopore sequencing runs on flow cell #3 with sample reloading, plotted as a function of elapsed time in hours since the start of flow cell sequencing. b Cumulative numbers of all sequenced reads (black line) and target viral reads (red line) from the nanopore run (left panel) or MiSeq run (right panel), plotted as a function of individual sequencing run time in minutes. c Taxonomic donut charts generated by real-time MetaPORE analysis of the nanopore reads (left panel) and post-run analysis of the MiSeq reads (right panel). The total number of reads analyzed is shown in the center of the donut. Note that given computational time constraints, only a subset of MiSeq reads (n = 100,000) was analyzed using MetaPORE. d Coverage and pairwise identity plots generated from nanopore (left panel) or MiSeq data (right panel) by mapping reads aligning to EBOV to the closest matching reference genome ((e), asterisk).  e Whole-genome phylogeny of EBOV. Representative EBOV genome sequences, including those from the 2014-2015 West Africa outbreak (tan) and 2014 DRC outbreak (pink), are included. Branch lengths are drawn proportionally to the number of nucleotide substitutions per position, and support values are shown for each node. Data were analyzed in MetaPORE on a 64-core Ubuntu Linux server using the January 2015 NT reference database.