SARS-CoV-2 Consensus Sequence Generation

Additional samples, not reported in this study, were included on Illumina NextSeq runs. The raw reads were demultiplexed using bcl2fastq (v2.20) (Illumina Inc.) to produce 311 FASTQ files for the run with the routine samples (112 SARS-CoV-2 samples and 3 negative controls) and the run with the rapid response samples (247 SARS-CoV-2 samples, 4 negative controls, and 2 positive controls) with only the relevant samples analysed in this paper. The reads were used to generate a consensus sequence for each sample using an adapted open source pipeline [15 ]. Briefly, the reads had adapters trimmed with TrimGalore [16 ] and were aligned to the Wuhan-Hu-1 reference genome (accession MN908947.3) using BWA-MEM (v0.7.17) [17 ]; the ARTIC amplicons were trimmed and a consensus built using iVAR (v.1.2.3) [18 (link)].