Simulation data for the validation of the Context Identification workflow
In order to validate the workflow's performance, an in silico simulation of ONT reads was done. First, ten available genomes were selected from NCBI. No ResFinder gene was encoded on any of these genomes. A custom Python script artificially inserts ten ResFinder genes into the genome. Using BadRead [version 0.4.1; (Wick 2019)], ONT reads are in silico simulated at different quality tiers. All simulations were performed using –error_model nanopore2023 and --qscore_model nanopore2023, except for the 'Perfect' tier, which utilized --error_model random and --qscore_model ideal. The simulated ONT reads were aligned against the artificially created genome using minimap2 [version 2.28; -ax map-ont, --secondary=no; (Li 2018, 2021)] to get precise coordinates of each read with respect to the genome. Those coordinates are overlaid with the known AMR insertion coordinates, resulting in a per-read ground truth of whether it encodes an AMR gene. The simulated ONT datasets are run through the workflow, and the results are compared to the ground truth for taxonomy and AMR encoding.
In order to validate the workflow's performance, an in silico simulation of ONT reads was done. First, ten available genomes were selected from NCBI. No ResFinder gene was encoded on any of these genomes. A custom Python script artificially inserts ten ResFinder genes into the genome. Using BadRead [version 0.4.1; (Wick 2019)], ONT reads are in silico simulated at different quality tiers. All simulations were performed using –error_model nanopore2023 and --qscore_model nanopore2023, except for the 'Perfect' tier, which utilized --error_model random and --qscore_model ideal. The simulated ONT reads were aligned against the artificially created genome using minimap2 [version 2.28; -ax map-ont, --secondary=no; (Li 2018, 2021)] to get precise coordinates of each read with respect to the genome. Those coordinates are overlaid with the known AMR insertion coordinates, resulting in a per-read ground truth of whether it encodes an AMR gene. The simulated ONT datasets are run through the workflow, and the results are compared to the ground truth for taxonomy and AMR encoding.
Timo Robbert Jan Dijkstra