CompaRNA - on-line benchmarks of RNA structure prediction methods
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Table of contents:

  1. Overview

  2. Performance Plots

  3. Performance of RNAalifold(20) - scored higher in this pairwise comparison

  4. Performance of MaxExpect - scored lower in this pairwise comparison

  5. Compile and download dataset for RNAalifold(20) & MaxExpect [.zip] - may take several seconds...


Overview

Metric RNAalifold(20) MaxExpect
MCC 0.753 > 0.674
Average MCC ± 95% Confidence Intervals 0.747 ± 0.122 > 0.667 ± 0.135
Sensitivity 0.656 < 0.670
Positive Predictive Value 0.869 > 0.683
Total TP 298 < 304
Total TN 51920 > 51818
Total FP 66 < 185
Total FP CONTRA 18 < 47
Total FP INCONS 27 < 94
Total FP COMP 21 < 44
Total FN 156 > 150
P-value 1.66062906821e-08

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Performance plots


  1. Comparison of performance of RNAalifold(20) and MaxExpect. Positive Predictive Value (PPV) is plotted against sensitivity. Each dot represents a single test of each method. See tables below for raw data (individual counts for RNAalifold(20) and MaxExpect).

  2. Average Matthews Correlation Coefficients (MCC) with 95% confidence intervals (CIs) were plotted for different RNA families, for which at least 3 members were present in the benchmarking dataset. 'n' denotes the number of MCCs used to calculate the average and CI. See tables below for raw data (individual counts for RNAalifold(20) and MaxExpect).

  3. Comparison of average Matthews Correlation Coefficients (MCCs) for RNAalifold(20) and MaxExpect. The whiskers correspond to 95% confidence intervals (CIs). 'n' denotes the number of MCCs used to calculate average MCCs and CIs. See tables below for raw data (individual counts for RNAalifold(20) and MaxExpect).

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Performance of RNAalifold(20) - scored higher in this pairwise comparison

1. Total counts & total scores for RNAalifold(20)

Total Base Pair Counts
Total TP 298
Total TN 51920
Total FP 66
Total FP CONTRA 18
Total FP INCONS 27
Total FP COMP 21
Total FN 156
Total Scores
MCC 0.753
Average MCC ± 95% Confidence Intervals 0.747 ± 0.122
Sensitivity 0.656
Positive Predictive Value 0.869
Nr of predictions 15

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2. Individual counts for RNAalifold(20) [ download as .csv ]

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
3A2K_C 0.98 0.95 1.00 21 1087 0 0 0 0 1
3GX2_A 0.92 0.86 1.00 24 1425 1 0 0 1 4
3IVN_B 0.86 0.78 0.95 18 884 1 1 0 0 5
3IZ4_A 0.65 0.48 0.87 46 25483 15 4 3 8 49
3JYV_7 0.97 0.95 1.00 19 1092 2 0 0 2 1
3LA5_A 0.87 0.76 1.00 19 935 0 0 0 0 6
3NPB_A 0.75 0.57 1.00 21 2257 4 0 0 4 16
3O58_3 0.42 0.36 0.50 8 4748 9 3 5 1 14
3PDR_A 0.92 0.88 0.96 44 4794 3 1 1 1 6
3RKF_A 0.81 0.71 0.94 17 848 1 0 1 0 7
3SD1_A 0.84 0.86 0.83 25 1503 5 4 1 0 4
4A1C_2 0.22 0.25 0.19 5 4490 23 5 16 2 15
4AOB_A 0.85 0.72 1.00 21 1416 2 0 0 2 8
4ENB_A 0.51 0.27 1.00 4 468 0 0 0 0 11
4ENC_A 0.63 0.40 1.00 6 490 0 0 0 0 9

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Performance of MaxExpect - scored lower in this pairwise comparison

1. Total counts & total scores for MaxExpect

Total Base Pair Counts
Total TP 304
Total TN 51818
Total FP 185
Total FP CONTRA 47
Total FP INCONS 94
Total FP COMP 44
Total FN 150
Total Scores
MCC 0.674
Average MCC ± 95% Confidence Intervals 0.667 ± 0.135
Sensitivity 0.670
Positive Predictive Value 0.683
Nr of predictions 15

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2. Individual counts for MaxExpect [ download as .csv ]

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
3A2K_C 0.47 0.50 0.46 11 1084 13 3 10 0 11
3GX2_A 0.93 0.89 0.96 25 1423 2 1 0 1 3
3IVN_B 0.91 0.83 1.00 19 884 0 0 0 0 4
3IZ4_A 0.61 0.61 0.62 58 25442 42 14 22 6 37
3JYV_7 0.48 0.45 0.53 9 1094 9 3 5 1 11
3LA5_A 0.91 0.84 1.00 21 933 0 0 0 0 4
3NPB_A 0.77 0.73 0.82 27 2245 10 0 6 4 10
3O58_3 0.40 0.50 0.33 11 4731 36 8 14 14 11
3PDR_A 0.92 0.90 0.94 45 4792 5 1 2 2 5
3RKF_A 0.91 0.83 1.00 20 846 0 0 0 0 4
3SD1_A 0.70 0.69 0.71 20 1505 8 3 5 0 9
4A1C_2 0.19 0.25 0.16 5 4484 41 10 17 14 15
4AOB_A 0.60 0.59 0.63 17 1410 11 4 6 1 12
4ENB_A 0.85 0.73 1.00 11 461 0 0 0 0 4
4ENC_A 0.36 0.33 0.42 5 484 8 0 7 1 10

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Matthews Correlation Coeffient, Sensitivity and Positive Predictive Value have been calculated based on the paper by Gardener & Giegerich, 2004.