Extended Data Fig. 10: Comparison of the performance of different prediction models and the screening results in the A549 and KYSE-30 cell lines.
From: Prime editor-based high-throughput screening reveals functional synonymous mutations in human cells
a–b, ROC analysis of DS Finder, SilVA, and CADD on 45 confirmed pathogenic mutations (positive controls) and 1,439 synonymous mutations without phenotypes from our screening (negative controls). The x-axis represents the false positive rate, and the y-axis represents the true positive rate. The red, dark blue, and green curves represent DS Finder, SilVA, and CADD, respectively. The test set in a contains 20 positive controls, excluding the mutations used in the SilVA training set and the test set in b consists of the 25 mutations used in the SilVA training set. c–f, Screening results analysis of three cell lines. Volcano plot illustrating the results of screening for functional synonymous and nonsynonymous mutations affecting cell fitness in A549 (c) and KYSE-30 (e). Blue and red dots denote depleted and enriched epegRNAs, respectively. Analyzing the correlation between three eBARs using zLFC in A549 (d) and KYSE-30 (f), following the same method as in Fig. 1d. The data were filtered according to the log2 fold change of a specific eBAR and the Pearson correlation of the zLFC of another pair of eBARs was investigated. The y-axis represents the Pearson correlation of the zLFC, while the x-axis indicates the specific threshold that the absolute value of the LFC must surpass. Red, green, and blue denote three individual eBARs: AGCA, CACT, and GCAG, respectively. g, Performance of DS Finder in three cell lines compared with CADD and SilVA. Each point on the graph represents a different dataset, totaling 10.
