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 0.600 > 0.514
Average MCC ± 95% Confidence Intervals 0.630 ± 0.104 > 0.523 ± 0.070
Sensitivity 0.538 > 0.315
Positive Predictive Value 0.674 < 0.846
Total TP 507 > 297
Total TN 131633 < 132034
Total FP 305 > 60
Total FP CONTRA 32 > 6
Total FP INCONS 213 > 48
Total FP COMP 60 > 6
Total FN 436 < 646
P-value 3.56938820447e-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. 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)).

  3. 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)).

  4. 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)).

  5. 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)).

  6. 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 507
Total TN 131633
Total FP 305
Total FP CONTRA 32
Total FP INCONS 213
Total FP COMP 60
Total FN 436
Total Scores
MCC 0.600
Average MCC ± 95% Confidence Intervals 0.630 ± 0.104
Sensitivity 0.538
Positive Predictive Value 0.674
Nr of predictions 30

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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
2KE6_A 0.86 0.84 0.89 16 1110 3 0 2 1 3
2KUR_A 0.85 0.81 0.89 17 1109 2 0 2 0 4
2KUU_A 0.82 0.76 0.89 16 1110 3 0 2 1 5
2KUV_A 0.83 0.77 0.89 17 1109 2 0 2 0 5
2KUW_A 0.90 0.86 0.95 18 1109 1 0 1 0 3
2L1F_A 0.93 0.88 1.00 21 2059 0 0 0 0 3
2L1F_B 0.94 0.88 1.00 22 2123 0 0 0 0 3
2L94_A 0.97 0.95 1.00 19 971 0 0 0 0 1
2LC8_A -0.01 0.00 0.00 0 1525 15 2 13 0 20
2XKV_B 0.51 0.50 0.53 10 4541 23 0 9 14 10
2XXA_G 0.47 0.43 0.53 18 5117 16 1 15 0 24
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
3W3S_B 0.87 0.78 0.97 31 4721 2 0 1 1 9
3ZEX_C 0.24 0.21 0.28 11 14157 42 1 27 14 41
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
4FRG_B 0.32 0.28 0.38 9 3462 15 0 15 0 23
4FRN_A 0.51 0.44 0.59 16 5124 11 3 8 0 20

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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 297
Total TN 132034
Total FP 60
Total FP CONTRA 6
Total FP INCONS 48
Total FP COMP 6
Total FN 646
Total Scores
MCC 0.514
Average MCC ± 95% Confidence Intervals 0.523 ± 0.070
Sensitivity 0.315
Positive Predictive Value 0.846
Nr of predictions 30

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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
2KE6_A 0.66 0.53 0.83 10 1116 2 0 2 0 9
2KUR_A 0.63 0.48 0.83 10 1116 2 0 2 0 11
2KUU_A 0.63 0.48 0.83 10 1116 2 0 2 0 11
2KUV_A 0.85 0.73 1.00 16 1112 0 0 0 0 6
2KUW_A 0.84 0.76 0.94 16 1111 1 0 1 0 5
2L1F_A 0.82 0.75 0.90 18 2060 2 0 2 0 6
2L1F_B 0.80 0.72 0.90 18 2125 2 0 2 0 7
2L94_A 0.59 0.40 0.89 8 981 1 0 1 0 12
2LC8_A -0.01 0.00 0.00 0 1528 12 0 12 0 20
2XKV_B 0.45 0.20 1.00 4 4556 2 0 0 2 16
2XXA_G 0.38 0.14 1.00 6 5145 0 0 0 0 36
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
3W3S_B 0.41 0.23 0.75 9 4741 3 0 3 0 31
3ZEX_C 0.37 0.13 1.00 7 14189 0 0 0 0 45
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
4FRG_B 0.15 0.09 0.25 3 3474 9 0 9 0 29
4FRN_A 0.58 0.39 0.88 14 5135 2 1 1 0 22

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