Extended Data Fig. 3: Comparison of base editing efficiencies induced by different CGBEs.
From: Deep learning models to predict the editing efficiencies and outcomes of diverse base editors
The red triangles indicate target sequences at which the editing efficiency of one base editor is at least 30% higher than that of the other base editor. Heatmaps show the relative distribution of nucleotides neighboring the target nucleotide in target sequences within the red triangles. Results at position 6 are also shown in Fig. 2d–f. The number of target sequences (n) = 1,807 and 830 at position 5, 1,413 and 957 at position 6, and 1,249 and 1,227 at position 7 for NG-CGBE1 and NG-miniCGBE1, respectively (a), 2,643 and 972 at position 5, 2,894 and 817 at position 6, 2,706 and 838 at position 7 for NG-miniCGBE1 and NG-APOBEC-nCas9-Ung, respectively (b), and 2,885 and 808 at position 5, 2,995 and 766 at position 6, and 2,715 and 891 at position 7 for NG-CGBE1 and NG-APOBEC-nCas9-Ung, respectively (c).
