Fig. 4

The effect of pipeline modifications, parameter changes, and combination strategies. We show the sensitivity for the prediction set with at least 90% precision. a Performance when applying local realignment around indels or the binomial test as a germline filter. b Performance of deepSNV, JointSNVMix2, SAMtools, and VarScan2 with different choices of parameters. Additional file 1: Figure H depicts the performance for all parameters that were assessed. c Performance of rank-combinations and intersections of calls from several tools. From each tool, we took the best version. In particular, deepSNV and MuTect with the binomial test as germline filter, SAMtools with option -C 200, SiNVICT with –qscore-cutoff 60, VarScan2 with the parameter –min-var-freq 0.02, as well as the default runs from GATK HP, GATK UG, JointSNVMix2, and somaticSniper. d Summary barplot displaying the performance of the three best rank-combinations as a comparison to each tool individually. If a tool parameter or pipeline change has been used in the rank-combinations, also the performance of the tool in default mode is shown. The y-axis measures the area under precision-recall curve when allowing a false discovery rate of up to 10% (see Additional file 1: Section C)