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

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric UNAFold Murlet(seed)
MCC 0.615 > 0.514
Average MCC ± 95% Confidence Intervals 0.646 ± 0.109 > 0.523 ± 0.070
Sensitivity 0.543 > 0.315
Positive Predictive Value 0.702 < 0.846
Total TP 512 > 297
Total TN 131656 < 132034
Total FP 287 > 60
Total FP CONTRA 21 > 6
Total FP INCONS 196 > 48
Total FP COMP 70 > 6
Total FN 431 < 646
P-value 3.56938820447e-08

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Performance plots


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

  2. Comparison of performance of UNAFold 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 UNAFold 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 UNAFold 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 UNAFold and Murlet(seed)).

  5. Comparison of average Matthews Correlation Coefficients (MCCs) for UNAFold 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 UNAFold and Murlet(seed)).

  6. Comparison of average Matthews Correlation Coefficients (MCCs) for UNAFold 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 UNAFold and Murlet(seed)).

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Performance of UNAFold - scored higher in this pairwise comparison

1. Total counts & total scores for UNAFold

Total Base Pair Counts
Total TP 512
Total TN 131656
Total FP 287
Total FP CONTRA 21
Total FP INCONS 196
Total FP COMP 70
Total FN 431
Total Scores
MCC 0.615
Average MCC ± 95% Confidence Intervals 0.646 ± 0.109
Sensitivity 0.543
Positive Predictive Value 0.702
Nr of predictions 30

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2. Individual counts for UNAFold [ 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 0.97 0.95 1.00 18 1110 1 0 0 1 1
2KUR_A 0.95 0.90 1.00 19 1109 0 0 0 0 2
2KUU_A 0.92 0.86 1.00 18 1110 1 0 0 1 3
2KUV_A 0.93 0.86 1.00 19 1109 0 0 0 0 3
2KUW_A 0.95 0.90 1.00 19 1109 0 0 0 0 2
2L1F_A 0.98 0.96 1.00 23 2057 0 0 0 0 1
2L1F_B 0.98 0.96 1.00 24 2121 0 0 0 0 1
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 0.47 0.45 0.50 9 4542 21 0 9 12 11
2XXA_G 0.34 0.31 0.39 13 5118 20 1 19 0 29
3A3A_A 0.87 0.76 1.00 28 3627 0 0 0 0 9
3GX2_A 0.68 0.55 0.85 22 4345 5 0 4 1 18
3IVN_B 0.78 0.61 1.00 19 2327 0 0 0 0 12
3JYX_4 0.32 0.30 0.34 10 12217 31 3 16 12 23
3LA5_A 0.78 0.62 1.00 21 2464 0 0 0 0 13
3NPB_A 0.78 0.65 0.94 30 6989 5 0 2 3 16
3O58_3 0.35 0.34 0.35 12 12369 33 1 21 11 23
3PDR_A 0.77 0.64 0.94 46 12831 5 0 3 2 26
3RKF_A 0.76 0.59 1.00 20 2191 0 0 0 0 14
3SD1_A 0.64 0.52 0.79 22 3888 6 1 5 0 20
3W3S_B 0.56 0.50 0.63 20 4721 13 1 11 1 20
3ZEX_C 0.24 0.21 0.28 11 14157 42 1 27 14 41
4A1C_2 0.14 0.15 0.14 5 11745 42 5 26 11 28
4AOB_A 0.50 0.40 0.63 17 4344 11 2 8 1 25
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 1 6 0 14
4FRG_B 0.32 0.28 0.38 9 3462 15 0 15 0 23
4FRN_A 0.43 0.36 0.52 13 5126 12 2 10 0 23

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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.