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 0.614 > 0.475
Average MCC ± 95% Confidence Intervals 0.623 ± 0.125 > 0.471 ± 0.083
Sensitivity 0.531 > 0.270
Positive Predictive Value 0.715 < 0.841
Total TP 291 > 148
Total TN 83826 < 84057
Total FP 157 > 32
Total FP CONTRA 18 > 5
Total FP INCONS 98 > 23
Total FP COMP 41 > 4
Total FN 257 < 400
P-value 2.22210847902e-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. 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)).

  3. 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 291
Total TN 83826
Total FP 157
Total FP CONTRA 18
Total FP INCONS 98
Total FP COMP 41
Total FN 257
Total Scores
MCC 0.614
Average MCC ± 95% Confidence Intervals 0.623 ± 0.125
Sensitivity 0.531
Positive Predictive Value 0.715
Nr of predictions 16

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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
2LC8_A 0.61 0.55 0.69 11 1524 5 0 5 0 9
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
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

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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.