Fig. 2: The performance comparison of HK model 1 and 2. | Communications Biology

Fig. 2: The performance comparison of HK model 1 and 2.

From: Transformer-based deep learning for accurate detection of multiple base modifications using single molecule real-time sequencing

Fig. 2: The performance comparison of HK model 1 and 2.

A Receiver Operating Characteristic (ROC) curves for the testing dataset on the basis of different models. B Area under ROC curve (AUC-ROC) values across different subread depths of SMRT-seq. Error bars represent one standard deviation of AUC among five repeated measurements. C Precision-Recall (PR) curves for the testing dataset on the basis of different models. D Area under PR curve (AUC-PR) values across different subread depths of SMRT-seq. Error bars represent one standard deviation of AUC among five repeated measurements. E Percentage of callable CpG sites at relative positions of DNA molecules. The grey area indicates the no-call region of the HK model 1. F ROC curve of HK model 2 for analyzing the CpG sites within the 10-nt distance relative to the nearest 5’ end of sequenced DNA fragments.

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