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

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric RNAfold Murlet(seed)
MCC 0.631 > 0.514
Average MCC ± 95% Confidence Intervals 0.671 ± 0.098 > 0.523 ± 0.070
Sensitivity 0.561 > 0.315
Positive Predictive Value 0.715 < 0.846
Total TP 529 > 297
Total TN 131645 < 132034
Total FP 283 > 60
Total FP CONTRA 23 > 6
Total FP INCONS 188 > 48
Total FP COMP 72 > 6
Total FN 414 < 646
P-value 3.56938820447e-08

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Performance plots


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

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

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

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

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Performance of RNAfold - scored higher in this pairwise comparison

1. Total counts & total scores for RNAfold

Total Base Pair Counts
Total TP 529
Total TN 131645
Total FP 283
Total FP CONTRA 23
Total FP INCONS 188
Total FP COMP 72
Total FN 414
Total Scores
MCC 0.631
Average MCC ± 95% Confidence Intervals 0.671 ± 0.098
Sensitivity 0.561
Positive Predictive Value 0.715
Nr of predictions 30

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2. Individual counts for RNAfold [ 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 0.61 0.55 0.69 11 1524 5 0 5 0 9
2XKV_B 0.51 0.50 0.53 10 4541 23 0 9 14 10
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 0.31 0.30 0.32 10 12215 33 5 16 12 23
3LA5_A 0.78 0.62 1.00 21 2464 0 0 0 0 13
3NPB_A 0.83 0.72 0.97 33 6987 4 0 1 3 13
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 0.64 0.52 0.79 22 3888 6 1 5 0 20
3W3S_B 0.55 0.50 0.61 20 4720 14 1 12 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 11744 43 5 27 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 0.52 0.44 0.62 16 5125 10 2 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.