Double-CRISPR Knockout Simulation (DKOsim): A Monte-Carlo randomization system to model cell growth behavior and infer the optimal library design for growth-based double knockout screens.

When 30% of the guides were highly efficient, 5 guides per gene with r = 0.8 is the optimum of the correlation; when either 50% and 80% of the guides were highly efficient, we observed an asymptotic optimum of the correlation at 3 guides per gene with 0.79 and 0.77, respectively; and when all of the guides were highly efficient, the correlation reached the optimum with r = 0.76 at 2 guides per gene and, unexpectedly, show a decreasing trend beyond this point, indicating dLFC might not identify the GI well in a perfect guide-efficacy scenario.

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When the systematic runs were restricted to compare guide quality by tuning the high-efficacy guides percentages at 100x coverage, the correlations between dLFC and simulated GIs with increasing percentage of high-efficacy guides from 10% to 100% showed an increasing trend, with r = 0.76 for 100% high-efficacy guides ( Fig 5D ).

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