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

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric Pknots Murlet(seed)
MCC 0.588 > 0.514
Average MCC ± 95% Confidence Intervals 0.662 ± 0.110 > 0.523 ± 0.070
Sensitivity 0.542 > 0.315
Positive Predictive Value 0.644 < 0.846
Total TP 511 > 297
Total TN 131592 < 132034
Total FP 328 > 60
Total FP CONTRA 40 > 6
Total FP INCONS 242 > 48
Total FP COMP 46 > 6
Total FN 432 < 646
P-value 3.56938820447e-08

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Performance plots


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

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

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

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

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Performance of Pknots - scored higher in this pairwise comparison

1. Total counts & total scores for Pknots

Total Base Pair Counts
Total TP 511
Total TN 131592
Total FP 328
Total FP CONTRA 40
Total FP INCONS 242
Total FP COMP 46
Total FN 432
Total Scores
MCC 0.588
Average MCC ± 95% Confidence Intervals 0.662 ± 0.110
Sensitivity 0.542
Positive Predictive Value 0.644
Nr of predictions 30

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2. Individual counts for Pknots [ 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 0.92 0.90 0.95 18 971 1 0 1 0 2
2LC8_A 0.79 0.75 0.83 15 1522 3 1 2 0 5
2XKV_B 0.23 0.25 0.22 5 4537 31 1 17 13 15
2XXA_G 0.32 0.31 0.34 13 5113 25 1 24 0 29
3A3A_A 0.87 0.76 1.00 28 3627 0 0 0 0 9
3GX2_A 0.47 0.40 0.55 16 4342 14 1 12 1 24
3IVN_B 0.78 0.65 0.95 20 2325 1 0 1 0 11
3JYX_4 0.18 0.21 0.16 7 12203 41 13 23 5 26
3LA5_A 0.80 0.65 1.00 22 2463 0 0 0 0 12
3NPB_A 0.76 0.67 0.86 31 6985 8 1 4 3 15
3O58_3 0.27 0.31 0.24 11 12357 38 11 24 3 24
3PDR_A 0.54 0.44 0.65 32 12831 19 0 17 2 40
3RKF_A 0.77 0.62 0.95 21 2189 1 0 1 0 13
3SD1_A 0.65 0.52 0.81 22 3889 5 0 5 0 20
3W3S_B 0.71 0.63 0.81 25 4722 7 0 6 1 15
3ZEX_C 0.07 0.08 0.07 4 14141 54 4 47 3 48
4A1C_2 0.24 0.24 0.25 8 11749 36 3 21 12 25
4AOB_A 0.17 0.14 0.21 6 4343 23 1 21 1 36
4ENB_A 0.83 0.79 0.88 15 1258 2 1 1 0 4
4ENC_A 0.86 0.79 0.94 15 1310 1 1 0 0 4
4FRG_B 0.48 0.38 0.63 12 3467 7 0 7 0 20
4FRN_A 0.51 0.42 0.63 15 5127 9 1 8 0 21

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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.