which pinpoints the necessity of modeling zero-inflation to derive more accurate error rates estimation. Furthermore, for SNVs with allele frequency greater than 1 %, the average recall is 97.5 % with 82.3 % average precision for ZINB GLM. To summarize, the performance evaluation results on low-frequency SNV identification also support the conclusion from Vuong’s non-nested test, with ZINB being the most appropriate model. Further, the necessity of modeling both dispersion and zero-inflation is exemplified by the much-elevated performance at close to sequencing error rate allele frequency, which is important for pushing down the detection limit of low-frequency SNV callers.
