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

  1. Overview

  2. Performance Plots

  3. Performance of TurboFold(seed) - scored higher in this pairwise comparison

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

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


Overview

Metric TurboFold(seed) RSpredict(seed)
MCC 0.529 > 0.213
Average MCC ± 95% Confidence Intervals 0.527 ± 0.155 > 0.170 ± 0.133
Sensitivity 0.434 > 0.092
Positive Predictive Value 0.650 > 0.500
Total TP 212 > 45
Total TN 79366 < 79602
Total FP 150 > 47
Total FP CONTRA 16 > 4
Total FP INCONS 98 > 41
Total FP COMP 36 > 2
Total FN 277 < 444
P-value 1.00475527001e-08

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Performance plots


  1. Comparison of performance of TurboFold(seed) and RSpredict(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 TurboFold(seed) and RSpredict(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 TurboFold(seed) and RSpredict(seed)).

  3. Comparison of average Matthews Correlation Coefficients (MCCs) for TurboFold(seed) and RSpredict(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 TurboFold(seed) and RSpredict(seed)).

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Performance of TurboFold(seed) - scored higher in this pairwise comparison

1. Total counts & total scores for TurboFold(seed)

Total Base Pair Counts
Total TP 212
Total TN 79366
Total FP 150
Total FP CONTRA 16
Total FP INCONS 98
Total FP COMP 36
Total FN 277
Total Scores
MCC 0.529
Average MCC ± 95% Confidence Intervals 0.527 ± 0.155
Sensitivity 0.434
Positive Predictive Value 0.650
Nr of predictions 14

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2. Individual counts for TurboFold(seed) [ download as .csv ]

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
2LC8_A -0.01 0.00 0.00 0 1525 15 2 13 0 20
3J3E_8 0.17 0.15 0.21 5 7479 28 2 17 9 28
3J3F_8 0.39 0.36 0.42 13 12215 32 2 16 14 23
3RKF_A 0.76 0.59 1.00 20 2191 0 0 0 0 14
3SD1_A 0.59 0.48 0.74 20 3889 7 1 6 0 22
3W1K_J 0.87 0.79 0.97 30 4155 1 1 0 0 8
3ZEX_C 0.39 0.27 0.56 14 14171 14 2 9 3 38
4A1C_3 0.69 0.57 0.84 31 7103 6 0 6 0 23
4A1C_2 0.15 0.15 0.15 5 11748 37 3 25 9 28
4AOB_A 0.56 0.40 0.77 17 4349 6 1 4 1 25
4ENB_A 0.69 0.47 1.00 9 1266 0 0 0 0 10
4ENC_A 0.65 0.47 0.90 9 1316 1 1 0 0 10
4FRN_A 0.69 0.56 0.87 20 5128 3 1 2 0 16
4JF2_A 0.78 0.61 1.00 19 2831 0 0 0 0 12

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Performance of RSpredict(seed) - scored lower in this pairwise comparison

1. Total counts & total scores for RSpredict(seed)

Total Base Pair Counts
Total TP 45
Total TN 79602
Total FP 47
Total FP CONTRA 4
Total FP INCONS 41
Total FP COMP 2
Total FN 444
Total Scores
MCC 0.213
Average MCC ± 95% Confidence Intervals 0.170 ± 0.133
Sensitivity 0.092
Positive Predictive Value 0.500
Nr of predictions 14

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2. Individual counts for RSpredict(seed) [ download as .csv ]

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
2LC8_A -0.01 0.00 0.00 0 1527 13 0 13 0 20
3J3E_8 0.00 0.00 0.00 0 7503 0 0 0 0 33
3J3F_8 0.14 0.06 0.33 2 12240 5 1 3 1 34
3RKF_A 0.71 0.53 0.95 18 2192 1 0 1 0 16
3SD1_A 0.00 0.00 0.00 0 3916 0 0 0 0 42
3W1K_J 0.51 0.29 0.92 11 4174 1 0 1 0 27
3ZEX_C 0.10 0.04 0.25 2 14188 6 1 5 0 50
4A1C_3 0.00 0.00 0.00 0 7136 4 1 3 0 54
4A1C_2 0.00 0.00 0.00 0 11777 5 1 3 1 33
4AOB_A 0.35 0.14 0.86 6 4364 1 0 1 0 36
4ENB_A 0.30 0.16 0.60 3 1270 2 0 2 0 16
4ENC_A 0.30 0.16 0.60 3 1321 2 0 2 0 16
4FRN_A 0.00 0.00 0.00 0 5148 3 0 3 0 36
4JF2_A 0.00 0.00 0.00 0 2846 4 0 4 0 31

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Matthews Correlation Coeffient, Sensitivity and Positive Predictive Value have been calculated based on the paper by Gardener & Giegerich, 2004.