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

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric Carnac(20) Murlet(seed)
MCC 0.629 > 0.564
Average MCC ± 95% Confidence Intervals 0.526 ± 0.165 < 0.561 ± 0.072
Sensitivity 0.426 > 0.366
Positive Predictive Value 0.935 > 0.876
Total TP 172 > 148
Total TN 38403 < 38418
Total FP 23 < 28
Total FP CONTRA 4 = 4
Total FP INCONS 8 < 17
Total FP COMP 11 > 7
Total FN 232 < 256
P-value 2.76499031155e-08

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Performance plots


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

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

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

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

Total Base Pair Counts
Total TP 172
Total TN 38403
Total FP 23
Total FP CONTRA 4
Total FP INCONS 8
Total FP COMP 11
Total FN 232
Total Scores
MCC 0.629
Average MCC ± 95% Confidence Intervals 0.526 ± 0.165
Sensitivity 0.426
Positive Predictive Value 0.935
Nr of predictions 16

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

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
3GX2_A 0.68 0.46 1.00 13 1436 0 0 0 0 15
3IVN_B 0.91 0.83 1.00 19 884 0 0 0 0 4
3J3E_8 0.00 0.00 0.00 0 2742 0 0 0 0 15
3J3F_8 0.61 0.37 1.00 7 4754 2 0 0 2 12
3LA5_A 0.91 0.84 1.00 21 933 0 0 0 0 4
3NPB_A 0.46 0.22 1.00 8 2270 3 0 0 3 29
3O58_3 0.60 0.36 1.00 8 4756 1 0 0 1 14
3PDR_A 0.75 0.58 0.97 29 4810 3 1 0 2 21
3RKF_A 0.91 0.83 1.00 20 846 0 0 0 0 4
3SD1_A 0.72 0.55 0.94 16 1516 1 0 1 0 13
3ZEX_C 0.37 0.21 0.67 6 5365 4 1 2 1 23
4A1C_2 0.42 0.25 0.71 5 4509 3 0 2 1 15
4AOB_A 0.59 0.48 0.74 14 1418 6 2 3 1 15
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 0.50 0.25 1.00 6 1196 0 0 0 0 18

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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 38418
Total FP 28
Total FP CONTRA 4
Total FP INCONS 17
Total FP COMP 7
Total FN 256
Total Scores
MCC 0.564
Average MCC ± 95% Confidence Intervals 0.561 ± 0.072
Sensitivity 0.366
Positive Predictive Value 0.876
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
3GX2_A 0.70 0.50 1.00 14 1435 1 0 0 1 14
3IVN_B 0.62 0.52 0.75 12 887 4 2 2 0 11
3J3E_8 0.36 0.13 1.00 2 2740 2 0 0 2 13
3J3F_8 0.61 0.37 1.00 7 4754 0 0 0 0 12
3LA5_A 0.67 0.56 0.82 14 937 3 1 2 0 11
3NPB_A 0.59 0.35 1.00 13 2265 2 0 0 2 24
3O58_3 0.52 0.27 1.00 6 4758 1 0 0 1 16
3PDR_A 0.53 0.28 1.00 14 4826 0 0 0 0 36
3RKF_A 0.62 0.50 0.80 12 851 3 1 2 0 12
3SD1_A 0.56 0.38 0.85 11 1520 2 0 2 0 18
3ZEX_C 0.49 0.24 1.00 7 5367 0 0 0 0 22
4A1C_2 0.59 0.35 1.00 7 4509 0 0 0 0 13
4AOB_A 0.69 0.48 1.00 14 1423 1 0 0 1 15
4ENB_A 0.63 0.40 1.00 6 466 0 0 0 0 9
4ENC_A 0.63 0.40 1.00 6 490 0 0 0 0 9
4FRG_B 0.17 0.13 0.25 3 1190 9 0 9 0 21

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