From: Deep learning improves the ability of sgRNA off-target propensity prediction
Test Set | Model | auROC | auPRC | Pearson value | Spearman value |
---|---|---|---|---|---|
Total test set | CnnCrispr | 0.975 | 0.679 | 0.682 | 0.154 |
CFD | 0.942 | 0.316 | 0.343 | 0.140 | |
MIT | 0.77 | 0.044 | 0.150 | 0.085 | |
CNN_std | 0.947 | 0.208 | 0.321 | 0.141 | |
DeepCrispr | 0.981 | 0.497 | – | 0.133 | |
Hek293t test set | CnnCrispr | 0.971 | 0.686 | 0.712 | 0.160 |
CFD | 0.936 | 0.318 | 0.371 | 0.143 | |
MIT | 0.756 | 0.048 | 0.153 | 0.084 | |
CNN_std | 0.939 | 0.204 | 0.330 | 0.144 | |
DeepCrispr | 0.984 | 0.521 | – | 0.136 | |
K562 test set | CnnCrispr | 0.995 | 0.688 | 0.426 | 0.134 |
CFD | 0.965 | 0.322 | 0.336 | 0.128 | |
MIT | 0.814 | 0.033 | 0.057 | 0.086 | |
CNN_std | 0.983 | 0.287 | 0.319 | 0.132 | |
DeepCrispr | 0.953 | 0.41 | – | 0.126 |