Fig. 2 |. Primer selection pipeline based on Optimal Prime (OP) models.

a, Overview of specificity and yield metrics derived to infer individual primer performance. b, Scatter plot depicting the correlation between the specificity metric (mean of FPB and OTF) and the yield metric (Normalized Log Total Amplification). Pearson correlation coefficient is given. c, Scatter plots depicting the correlation between various individual features thought to be important for determining primer performance and the specificity metric (mean of FPB and OTF) or the yield metric (Normalized Log Total Amplification). Pearson correlation coefficients are given and definitions of individual features are provided in Supplementary Table 2. d, Overview of processing steps in final primer selection pipeline. Pipeline allows use of either the “full” or “lite” specificity and yield models. e, Overview of encoded sequence-based features. Individual LSV-seq primer is shown as it would bind to the RNA during reverse transcription, along with the proximal region extended by the reverse transcriptase. f, Cross-validated performance of trained regression models. For each indicated model type, the calculated R2 score and Pearson correlation are given based on held-out 5-fold cross-validation splits conducted independently twice.