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

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric RNAshapes Murlet(seed)
MCC 0.640 > 0.514
Average MCC ± 95% Confidence Intervals 0.678 ± 0.094 > 0.523 ± 0.070
Sensitivity 0.568 > 0.315
Positive Predictive Value 0.726 < 0.846
Total TP 536 > 297
Total TN 131647 < 132034
Total FP 270 > 60
Total FP CONTRA 22 > 6
Total FP INCONS 180 > 48
Total FP COMP 68 > 6
Total FN 407 < 646
P-value 3.56938820447e-08

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Performance plots


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

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

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

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

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Performance of RNAshapes - scored higher in this pairwise comparison

1. Total counts & total scores for RNAshapes

Total Base Pair Counts
Total TP 536
Total TN 131647
Total FP 270
Total FP CONTRA 22
Total FP INCONS 180
Total FP COMP 68
Total FN 407
Total Scores
MCC 0.640
Average MCC ± 95% Confidence Intervals 0.678 ± 0.094
Sensitivity 0.568
Positive Predictive Value 0.726
Nr of predictions 30

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2. Individual counts for RNAshapes [ 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 0.87 0.83 0.91 20 2058 2 0 2 0 4
2L1F_B 0.96 0.92 1.00 23 2122 0 0 0 0 2
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 22 0 9 13 10
2XXA_G 0.93 0.86 1.00 36 5115 0 0 0 0 6
3A3A_A 0.76 0.65 0.89 24 3628 3 0 3 0 13
3GX2_A 0.76 0.63 0.93 25 4344 3 0 2 1 15
3IVN_B 0.78 0.61 1.00 19 2327 0 0 0 0 12
3JYX_4 0.31 0.30 0.31 10 12214 35 5 17 13 23
3LA5_A 0.76 0.59 1.00 20 2465 0 0 0 0 14
3NPB_A 0.77 0.63 0.94 29 6990 4 1 1 2 17
3O58_3 0.34 0.34 0.34 12 12368 37 2 21 14 23
3PDR_A 0.67 0.56 0.80 40 12830 12 0 10 2 32
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 0.48 0.63 19 4723 12 1 10 1 21
3ZEX_C 0.23 0.21 0.25 11 14152 41 1 32 8 41
4A1C_2 0.14 0.15 0.14 5 11746 41 5 25 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.