CRISPR-Analytics (CRISPR-A): A platform for precise analytics and simulations for gene editing
Fig 2
Indels characterization algorithm development and benchmark with simulated data and real data.
A) Accuracy of indels detection after aligning with different alignment tools. We have used 139 samples simulated from different reference sequences and cut site location with SimGE. The accuracy, which is the number of reads correctly classified against all classified reads, has been calculated after characterizing the indels and wt sequences of each sample after aligning the samples with 6 different methods. The mean and standard deviation of the accuracy of the different characterized samples by alignment method are represented in the plot. B) Optimization of alignment penalty matrix. Best parameters have been determined through Monte Carlo to obtain alignments optimal for CRISPR-based indels characterization. In the PCA we can see how the four parameters of the alignment penalty matrix should be combined to achieve higher accuracy. C) Benchmarking of indels characterization between 6 different tools. CRISPR-A is compared with 5 other tools using a simulated data set of 139 samples. All samples contain the same percentage of indels (red dashed line) and the violin plot shows us the dispersion of the reported editing percentages by each tool. D) Reported editing of edited t-cells. 1656 unique edited genomic locations within 559 genes are characterized with 6 different tools. The percentage of editing reported by each tool for each sample is shown by the heatmap. E) Error characterization from the most discrepant values in t-cell edited samples. CRISPR-A results are compared with the results of other tools with more distant results (example at left side; explored samples are encircled in red). Errors are classified regarding their source.