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Table 2 Results of Task 2.

From: A community assessment of privacy preserving techniques for human genomes

  Teams Top 1 Top 3 Top 5 Top 10 Top 15 Top 20 Top 30
Small (5000 SNVs) UT Austin
CMU
1
0.98
2.66
2.28
4.44
3.53
8.48
7.89
7.07
4.59
4.68
2.32
2.37
1.16
Large (100K SNVs) UT Austin
CMU
1
0.98
2.65
2.26
4.41
3.56
5.90
3.27
2.26
0.42
0.69
0.15
0.18
0.07
  1. The table shows the average number of (1000 iterations) privacy-preserving SNV identification algorithms developed by the two participating teams. Both algorithms were trained using the small dataset consisting of 5000 SNVs, and then were tested on both small and large datasets, i.e., select top K (i.e., K = 1, 3, ..., 30) most significant SNVs.