, using repeated sequencing of the same isolates (replicates) and data from consecutive infection isolates from six English hospitals. Hash-cgMLST provided the same results as standard cgMLST, with minimal performance penalty. Comparing 272 replicate sequence pairs using reference-based mapping, there were 0, 1, or 2 single-nucleotide polymorphisms (SNPs) between 262 (96%), 5 (2%), and 1 (<1%) of the pairs, respectively. Using hash-cgMLST, 218 (80%) of replicate pairs assembled with SPAdes had zero gene differences, and 31 (11%), 5 (2%), and 18 (7%) pairs had 1, 2, and >2 differences, respectively. False gene differences were clustered in specific genes and associated with fragmented assemblies, but were reduced using the SKESA assembler. Considering 412 pairs of infections with ≤2 SNPS, i.e., consistent with recent transmission, 376 (91%) had ≤2 gene differences and 16 (4%) had ≥4. Comparing a genome to 100,000 others took <1 min using hash-cgMLST. Hash-cgMLST is an effective surveillance tool for rapidly identifying clusters of related genomes. However, cgMLST/hash-cgMLST generate more false variants than mapping-based approaches. Follow-up mapping-based analyses are likely required to precisely define close genetic relationships.
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Eyre et al. (2019) studied this question.
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