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

  1. Overview

  2. Performance Plots

  3. Performance of RNAsubopt - scored higher in this pairwise comparison

  4. Performance of Murlet(seed) - scored lower in this pairwise comparison

  5. Compile and download dataset for RNAsubopt & Murlet(seed) [.zip] - may take several seconds...


Overview

Metric RNAsubopt Murlet(seed)
MCC 0.551 > 0.475
Average MCC ± 95% Confidence Intervals 0.554 ± 0.153 > 0.471 ± 0.083
Sensitivity 0.485 > 0.270
Positive Predictive Value 0.630 < 0.841
Total TP 266 > 148
Total TN 83811 < 84057
Total FP 185 > 32
Total FP CONTRA 27 > 5
Total FP INCONS 129 > 23
Total FP COMP 29 > 4
Total FN 282 < 400
P-value 2.59578924681e-08

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Performance plots


  1. Comparison of performance of RNAsubopt and Murlet(seed). 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 RNAsubopt and Murlet(seed)).

  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 RNAsubopt and Murlet(seed)).

  3. Comparison of average Matthews Correlation Coefficients (MCCs) for RNAsubopt and Murlet(seed). 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 RNAsubopt and Murlet(seed)).

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Performance of RNAsubopt - scored higher in this pairwise comparison

1. Total counts & total scores for RNAsubopt

Total Base Pair Counts
Total TP 266
Total TN 83811
Total FP 185
Total FP CONTRA 27
Total FP INCONS 129
Total FP COMP 29
Total FN 282
Total Scores
MCC 0.551
Average MCC ± 95% Confidence Intervals 0.554 ± 0.153
Sensitivity 0.485
Positive Predictive Value 0.630
Nr of predictions 16

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

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
2KDQ_B 0.95 0.91 1.00 10 396 0 0 0 0 1
2LC8_A -0.01 0.00 0.00 0 1525 15 2 13 0 20
3A3A_A 0.87 0.76 1.00 28 3627 0 0 0 0 9
3GX2_A 0.44 0.38 0.54 15 4343 14 1 12 1 25
3IVN_B 0.76 0.58 1.00 18 2328 0 0 0 0 13
3JYX_4 0.19 0.21 0.17 7 12204 38 11 24 3 26
3LA5_A 0.78 0.62 1.00 21 2464 0 0 0 0 13
3NPB_A 0.75 0.65 0.86 30 6986 7 1 4 2 16
3O58_3 0.34 0.34 0.34 12 12368 34 2 21 11 23
3PDR_A 0.75 0.63 0.90 45 12830 7 1 4 2 27
3RKF_A 0.76 0.59 1.00 20 2191 0 0 0 0 14
3SD1_A 0.61 0.50 0.75 21 3888 7 1 6 0 21
4A1C_2 0.14 0.15 0.13 5 11742 43 5 29 9 28
4AOB_A 0.52 0.43 0.64 18 4343 11 2 8 1 24
4ENB_A 0.70 0.58 0.85 11 1262 2 1 1 0 8
4ENC_A 0.32 0.26 0.42 5 1314 7 0 7 0 14

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Performance of Murlet(seed) - scored lower in this pairwise comparison

1. Total counts & total scores for Murlet(seed)

Total Base Pair Counts
Total TP 148
Total TN 84057
Total FP 32
Total FP CONTRA 5
Total FP INCONS 23
Total FP COMP 4
Total FN 400
Total Scores
MCC 0.475
Average MCC ± 95% Confidence Intervals 0.471 ± 0.083
Sensitivity 0.270
Positive Predictive Value 0.841
Nr of predictions 16

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2. Individual counts for Murlet(seed) [ download as .csv ]

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
2KDQ_B 0.52 0.27 1.00 3 403 0 0 0 0 8
2LC8_A -0.01 0.00 0.00 0 1528 12 0 12 0 20
3A3A_A 0.57 0.32 1.00 12 3643 0 0 0 0 25
3GX2_A 0.59 0.35 1.00 14 4357 1 0 0 1 26
3IVN_B 0.53 0.39 0.75 12 2330 4 2 2 0 19
3JYX_4 0.23 0.09 0.60 3 12241 4 0 2 2 30
3LA5_A 0.58 0.41 0.82 14 2468 3 1 2 0 20
3NPB_A 0.49 0.28 0.87 13 7006 2 1 1 0 33
3O58_3 0.45 0.20 1.00 7 12396 0 0 0 0 28
3PDR_A 0.44 0.19 1.00 14 12866 0 0 0 0 58
3RKF_A 0.53 0.35 0.80 12 2196 3 1 2 0 22
3SD1_A 0.47 0.26 0.85 11 3903 2 0 2 0 31
4A1C_2 0.46 0.21 1.00 7 11774 0 0 0 0 26
4AOB_A 0.58 0.33 1.00 14 4357 1 0 0 1 28
4ENB_A 0.56 0.32 1.00 6 1269 0 0 0 0 13
4ENC_A 0.56 0.32 1.00 6 1320 0 0 0 0 13

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