Supplementary Figure 8: Power analysis of larger genetic surveys.

By assuming lognormal tumor size distributions, the statistical power of Tuba-seq to detect driver growth effects and non-additive driver interactions in larger genetic surveys can be projected. Future experiments could utilize larger mouse cohorts and larger pools of sgRNAs targeting putative tumor suppressors. In all hypothetical experiments, the Lenti-sgTS-Pool/Cre titers and fraction of the pool with inert sgRNAs (for normalization) were kept consistent with our original experiments. a. P-value contours for the confidence in detecting a weak driver (parameterized by the sgCdkn2a distribution in KT;Cas9 mice). Any experimental setups above a contour detects weak drivers with a confidence greater than or equal to the P-value of the contour. b,c. Same as in a, except for moderate and strong drivers respectively (parameterized by sgRb1 and sgLkb1 in KT;Cas9 mice). sgRNA pool size is extended to 500 targets (instead of 100 targets in a pool) because larger screens are possible when investigating genes with these effect strengths. d-f. Same as in a-c, except for driver interactions. Driver interactions (LN Mean Ratio) are defined as a ratio of driver growth rates (sgTS/sgInert in background #1)/(sgTS/sgInert in background #2) that were statistically different from the null hypothesis of one. (d) A weak driver interaction parameterized by Rbm10—p53 (7% effect size). (e) A moderate driver interaction parameterized by Rb1—p53 (13% effect size). (f) A strong driver interaction parameterized by Setd2—Lkb1 (68% effect size).