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

  1. Overview

  2. Performance Plots

  3. Performance of Murlet(20) - scored higher in this pairwise comparison

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

  5. Compile and download dataset for Murlet(20) & Carnac(seed) [.zip] - may take several seconds...


Overview

Metric Murlet(20) Carnac(seed)
MCC 0.619 > 0.000
Average MCC ± 95% Confidence Intervals 0.594 ± 0.122 > 0.000 ± 0.000
Sensitivity 0.527 > 0.000
Positive Predictive Value 0.734 > 0.000
Total TP 213 > 0
Total TN 38297 < 38587
Total FP 105 > 0
Total FP CONTRA 21 > 0
Total FP INCONS 56 > 0
Total FP COMP 28 > 0
Total FN 191 < 404
P-value 2.7402423548e-08

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Performance plots


  1. Comparison of performance of Murlet(20) and Carnac(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 Murlet(20) and Carnac(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 Murlet(20) and Carnac(seed)).

  3. Comparison of average Matthews Correlation Coefficients (MCCs) for Murlet(20) and Carnac(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 Murlet(20) and Carnac(seed)).

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Performance of Murlet(20) - scored higher in this pairwise comparison

1. Total counts & total scores for Murlet(20)

Total Base Pair Counts
Total TP 213
Total TN 38297
Total FP 105
Total FP CONTRA 21
Total FP INCONS 56
Total FP COMP 28
Total FN 191
Total Scores
MCC 0.619
Average MCC ± 95% Confidence Intervals 0.594 ± 0.122
Sensitivity 0.527
Positive Predictive Value 0.734
Nr of predictions 16

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2. Individual counts for Murlet(20) [ download as .csv ]

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
3GX2_A 0.73 0.54 1.00 15 1434 1 0 0 1 13
3IVN_B 0.80 0.65 1.00 15 888 0 0 0 0 8
3J3E_8 0.35 0.33 0.38 5 2729 13 2 6 5 10
3J3F_8 0.54 0.53 0.56 10 4743 13 2 6 5 9
3LA5_A 0.80 0.64 1.00 16 938 0 0 0 0 9
3NPB_A 0.65 0.43 1.00 16 2262 2 0 0 2 21
3O58_3 0.37 0.32 0.44 7 4748 13 4 5 4 15
3PDR_A 0.84 0.76 0.93 38 4799 3 1 2 0 12
3RKF_A 0.81 0.67 1.00 16 850 0 0 0 0 8
3SD1_A 0.82 0.83 0.83 24 1504 5 4 1 0 5
3ZEX_C 0.42 0.38 0.48 11 5351 16 2 10 4 18
4A1C_2 0.22 0.25 0.20 5 4491 24 5 15 4 15
4AOB_A 0.87 0.76 1.00 22 1415 3 0 0 3 7
4ENB_A 0.51 0.27 1.00 4 468 0 0 0 0 11
4ENC_A 0.57 0.33 1.00 5 491 0 0 0 0 10
4FRG_B 0.19 0.17 0.25 4 1186 12 1 11 0 20

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

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

Total Base Pair Counts
Total TP 0
Total TN 38587
Total FP 0
Total FP CONTRA 0
Total FP INCONS 0
Total FP COMP 0
Total FN 404
Total Scores
MCC 0.000
Average MCC ± 95% Confidence Intervals 0.000 ± 0.000
Sensitivity 0.000
Positive Predictive Value 0.000
Nr of predictions 16

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

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
3GX2_A 0.00 0.00 0.00 0 1449 0 0 0 0 28
3IVN_B 0.00 0.00 0.00 0 903 0 0 0 0 23
3J3E_8 0.00 0.00 0.00 0 2742 0 0 0 0 15
3J3F_8 0.00 0.00 0.00 0 4761 0 0 0 0 19
3LA5_A 0.00 0.00 0.00 0 954 0 0 0 0 25
3NPB_A 0.00 0.00 0.00 0 2278 0 0 0 0 37
3O58_3 0.00 0.00 0.00 0 4764 0 0 0 0 22
3PDR_A 0.00 0.00 0.00 0 4840 0 0 0 0 50
3RKF_A 0.00 0.00 0.00 0 866 0 0 0 0 24
3SD1_A 0.00 0.00 0.00 0 1533 0 0 0 0 29
3ZEX_C 0.00 0.00 0.00 0 5374 0 0 0 0 29
4A1C_2 0.00 0.00 0.00 0 4516 0 0 0 0 20
4AOB_A 0.00 0.00 0.00 0 1437 0 0 0 0 29
4ENB_A 0.00 0.00 0.00 0 472 0 0 0 0 15
4ENC_A 0.00 0.00 0.00 0 496 0 0 0 0 15
4FRG_B 0.00 0.00 0.00 0 1202 0 0 0 0 24

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