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Table 1 Comparison of SpliceJumper, TopHat2 and MapSplice2 on simulation data.

From: SpliceJumper: a classification-based approach for calling splicing junctions from RNA-seq data

Slack value Test1 dataset   Test2 dataset  
  SpliceJumper TopHat2 MapSplice2 SpliceJumper TopHat2 MapSplice2
0 0.8314 0.0003 0.8918 0.7940 0.0015 0.8288
1 0.8923 0.0016 0.9627 0.8548 0.0103 0.9319
2 0.9367 0.9370 0.9631 0.9156 0.8558 0.9328
3 0.9618 0.9377 0.9639 0.9400 0.9016 0.9471
4 0.9666 0.9384 0.9642 0.9491 0.9150 0.9473
5 0.9676 0.9390 0.9647 0.9495 0.9156 0.9476
6 0.9676 0.9396 0.9650 0.9562 0.9166 0.9485
7 0.9676 0.9397 0.9650 0.9573 0.9167 0.9502
8 0.9676 0.9397 0.9651 0.9578 0.9178 0.9508
9 0.9677 0.9397 0.9651 0.9578 0.9178 0.9508
10 0.9677 0.9398 0.9651 0.9578 0.9178 0.9508
11 0.9677 0.9398 0.9651 0.9578 0.9179 0.9510
12 0.9678 0.9399 0.9651 0.9578 0.9179 0.9510
13 0.9678 0.9399 0.9652 0.9579 0.9180 0.9510
14 0.9678 0.9399 0.9652 0.9579 0.9180 0.9510
15 0.9678 0.9400 0.9653 0.9579 0.9180 0.9510
  1. Slack value is introduced when comparing a called out junction with a benchmarked one. And if the distance of both sides between the called out one and the benchmarked one is within the slack value then the called out one is considered as a correct one. We compare the F-value (2*Precision*Recall/(Precision+Recall)) of the three tools for different slack values. The higher the F-value the better the performance.