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Table of contents:
- Overview
- Performance Plots
- Performance of Murlet(20) - scored higher in this pairwise comparison
- Performance of Mastr(20) - scored lower in this pairwise comparison
- Compile and download dataset for Murlet(20) & Mastr(20) [.zip] - may take several seconds...
Overview
| Metric | Murlet(20) | Mastr(20) | |
|---|---|---|---|
| MCC | 0.590 | > | 0.500 |
| Average MCC ± 95% Confidence Intervals | 0.587 ± 0.059 | > | 0.458 ± 0.108 |
| Sensitivity | 0.438 | > | 0.336 |
| Positive Predictive Value | 0.799 | > | 0.749 |
| Total TP | 658 | > | 506 |
| Total TN | 283883 | < | 284031 |
| Total FP | 210 | > | 202 |
| Total FP CONTRA | 17 | < | 19 |
| Total FP INCONS | 149 | < | 151 |
| Total FP COMP | 44 | > | 32 |
| Total FN | 846 | < | 998 |
| P-value | 3.56938820447e-08 | ||
Performance plots
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Comparison of performance of Murlet(20) and Mastr(20). 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 Mastr(20)).
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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 Mastr(20)).
-
Comparison of average Matthews Correlation Coefficients (MCCs) for Murlet(20) and Mastr(20). 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 Mastr(20)).
Performance of Murlet(20) - scored higher in this pairwise comparison
1. Total counts & total scores for Murlet(20)
| Total Base Pair Counts | |
|---|---|
| Total TP | 658 |
| Total TN | 283883 |
| Total FP | 210 |
| Total FP CONTRA | 17 |
| Total FP INCONS | 149 |
| Total FP COMP | 44 |
| Total FN | 846 |
| Total Scores | |
|---|---|
| MCC | 0.590 |
| Average MCC ± 95% Confidence Intervals | 0.587 ± 0.059 |
| Sensitivity | 0.438 |
| Positive Predictive Value | 0.799 |
| Nr of predictions | 38 |
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 |
| 2KDQ_B | 0.67 | 0.45 | 1.00 | 5 | 401 | 0 | 0 | 0 | 0 | 6 | |
| 2WRQ_Y | 0.41 | 0.41 | 0.41 | 7 | 2833 | 12 | 6 | 4 | 2 | 10 | |
| 2XQD_Y | 0.80 | 0.70 | 0.90 | 19 | 2829 | 2 | 0 | 2 | 0 | 8 | |
| 3A2K_C | 0.78 | 0.68 | 0.90 | 19 | 2905 | 2 | 0 | 2 | 0 | 9 | |
| 3AMU_B | 0.77 | 0.67 | 0.90 | 18 | 2983 | 3 | 0 | 2 | 1 | 9 | |
| 3G4S_9 | 0.58 | 0.39 | 0.88 | 22 | 7356 | 3 | 1 | 2 | 0 | 35 | |
| 3GX2_A | 0.61 | 0.38 | 1.00 | 15 | 4356 | 1 | 0 | 0 | 1 | 25 | |
| 3IVN_B | 0.69 | 0.48 | 1.00 | 15 | 2331 | 0 | 0 | 0 | 0 | 16 | |
| 3IZ4_A | 0.40 | 0.24 | 0.65 | 32 | 70827 | 21 | 1 | 16 | 4 | 100 | |
| 3IZF_C | 0.71 | 0.56 | 0.91 | 30 | 6870 | 4 | 0 | 3 | 1 | 24 | |
| 3J20_0 | 0.58 | 0.47 | 0.74 | 14 | 2831 | 5 | 0 | 5 | 0 | 16 | |
| 3J20_1 | 0.68 | 0.57 | 0.81 | 13 | 2910 | 3 | 0 | 3 | 0 | 10 | |
| 3J2L_3 | 0.69 | 0.49 | 0.96 | 26 | 7848 | 3 | 0 | 1 | 2 | 27 | |
| 3J3D_C | 0.78 | 0.64 | 0.95 | 18 | 2756 | 1 | 0 | 1 | 0 | 10 | |
| 3J3E_7 | 0.77 | 0.63 | 0.94 | 34 | 7104 | 2 | 0 | 2 | 0 | 20 | |
| 3J3E_8 | 0.24 | 0.15 | 0.38 | 5 | 7490 | 13 | 1 | 7 | 5 | 28 | |
| 3J3F_7 | 0.69 | 0.50 | 0.96 | 25 | 7234 | 1 | 0 | 1 | 0 | 25 | |
| 3J3F_8 | 0.48 | 0.36 | 0.65 | 13 | 12226 | 10 | 0 | 7 | 3 | 23 | |
| 3J3V_B | 0.63 | 0.40 | 1.00 | 23 | 6998 | 0 | 0 | 0 | 0 | 34 | |
| 3JYV_7 | 0.67 | 0.53 | 0.85 | 17 | 2830 | 3 | 0 | 3 | 0 | 15 | |
| 3JYX_4 | 0.36 | 0.27 | 0.47 | 9 | 12227 | 15 | 0 | 10 | 5 | 24 | |
| 3JYX_3 | 0.60 | 0.52 | 0.70 | 14 | 6308 | 11 | 0 | 6 | 5 | 13 | |
| 3LA5_A | 0.68 | 0.47 | 1.00 | 16 | 2469 | 0 | 0 | 0 | 0 | 18 | |
| 3NPB_A | 0.55 | 0.35 | 0.89 | 16 | 7003 | 2 | 1 | 1 | 0 | 30 | |
| 3O58_2 | 0.89 | 0.82 | 0.97 | 31 | 7228 | 2 | 0 | 1 | 1 | 7 | |
| 3O58_3 | 0.33 | 0.23 | 0.47 | 8 | 12386 | 12 | 2 | 7 | 3 | 27 | |
| 3PDR_A | 0.70 | 0.53 | 0.93 | 38 | 12839 | 3 | 0 | 3 | 0 | 34 | |
| 3RKF_A | 0.68 | 0.47 | 1.00 | 16 | 2195 | 0 | 0 | 0 | 0 | 18 | |
| 3SD1_A | 0.68 | 0.57 | 0.83 | 24 | 3887 | 5 | 1 | 4 | 0 | 18 | |
| 3ZEX_D | 0.77 | 0.65 | 0.91 | 32 | 6986 | 3 | 0 | 3 | 0 | 17 | |
| 3ZEX_C | 0.34 | 0.23 | 0.50 | 12 | 14172 | 15 | 1 | 11 | 3 | 40 | |
| 3ZND_W | 0.45 | 0.39 | 0.53 | 9 | 2986 | 11 | 0 | 8 | 3 | 14 | |
| 4A1C_2 | 0.17 | 0.15 | 0.20 | 5 | 11756 | 24 | 2 | 18 | 4 | 28 | |
| 4A1C_3 | 0.59 | 0.41 | 0.85 | 22 | 7114 | 4 | 0 | 4 | 0 | 32 | |
| 4AOB_A | 0.72 | 0.55 | 0.96 | 23 | 4347 | 2 | 0 | 1 | 1 | 19 | |
| 4ENB_A | 0.46 | 0.21 | 1.00 | 4 | 1271 | 0 | 0 | 0 | 0 | 15 | |
| 4ENC_A | 0.51 | 0.26 | 1.00 | 5 | 1321 | 0 | 0 | 0 | 0 | 14 | |
| 4FRG_B | 0.17 | 0.13 | 0.25 | 4 | 3470 | 12 | 1 | 11 | 0 | 28 |
Performance of Mastr(20) - scored lower in this pairwise comparison
1. Total counts & total scores for Mastr(20)
| Total Base Pair Counts | |
|---|---|
| Total TP | 506 |
| Total TN | 284031 |
| Total FP | 202 |
| Total FP CONTRA | 19 |
| Total FP INCONS | 151 |
| Total FP COMP | 32 |
| Total FN | 998 |
| Total Scores | |
|---|---|
| MCC | 0.500 |
| Average MCC ± 95% Confidence Intervals | 0.458 ± 0.108 |
| Sensitivity | 0.336 |
| Positive Predictive Value | 0.749 |
| Nr of predictions | 38 |
2. Individual counts for Mastr(20) [ 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 | |
| 2WRQ_Y | 0.57 | 0.59 | 0.56 | 10 | 2832 | 12 | 5 | 3 | 4 | 7 | |
| 2XQD_Y | 0.88 | 0.78 | 1.00 | 21 | 2829 | 0 | 0 | 0 | 0 | 6 | |
| 3A2K_C | 0.72 | 0.61 | 0.85 | 17 | 2906 | 3 | 0 | 3 | 0 | 11 | |
| 3AMU_B | 0.77 | 0.59 | 1.00 | 16 | 2987 | 1 | 0 | 0 | 1 | 11 | |
| 3G4S_9 | 0.48 | 0.32 | 0.75 | 18 | 7357 | 8 | 1 | 5 | 2 | 39 | |
| 3GX2_A | 0.39 | 0.28 | 0.55 | 11 | 4351 | 10 | 0 | 9 | 1 | 29 | |
| 3IVN_B | 0.78 | 0.65 | 0.95 | 20 | 2325 | 1 | 1 | 0 | 0 | 11 | |
| 3IZ4_A | 0.00 | 0.00 | 0.00 | 0 | 70876 | 0 | 0 | 0 | 0 | 132 | |
| 3IZF_C | 0.73 | 0.63 | 0.85 | 34 | 6863 | 7 | 1 | 5 | 1 | 20 | |
| 3J20_0 | 0.84 | 0.70 | 1.00 | 21 | 2829 | 1 | 0 | 0 | 1 | 9 | |
| 3J20_1 | 0.25 | 0.22 | 0.29 | 5 | 2909 | 12 | 0 | 12 | 0 | 18 | |
| 3J2L_3 | 0.34 | 0.25 | 0.48 | 13 | 7848 | 16 | 1 | 13 | 2 | 40 | |
| 3J3D_C | 0.82 | 0.71 | 0.95 | 20 | 2754 | 1 | 0 | 1 | 0 | 8 | |
| 3J3E_7 | 0.66 | 0.57 | 0.76 | 31 | 7099 | 10 | 1 | 9 | 0 | 23 | |
| 3J3E_8 | 0.00 | 0.00 | 0.00 | 0 | 7503 | 0 | 0 | 0 | 0 | 33 | |
| 3J3F_7 | 0.72 | 0.64 | 0.82 | 32 | 7221 | 8 | 0 | 7 | 1 | 18 | |
| 3J3F_8 | 0.00 | 0.00 | 0.00 | 0 | 12246 | 0 | 0 | 0 | 0 | 36 | |
| 3J3V_B | 0.19 | 0.12 | 0.30 | 7 | 6998 | 16 | 0 | 16 | 0 | 50 | |
| 3JYV_7 | 0.81 | 0.66 | 1.00 | 21 | 2829 | 0 | 0 | 0 | 0 | 11 | |
| 3JYX_4 | 0.00 | 0.00 | 0.00 | 0 | 12246 | 0 | 0 | 0 | 0 | 33 | |
| 3JYX_3 | 0.56 | 0.56 | 0.58 | 15 | 6302 | 23 | 1 | 10 | 12 | 12 | |
| 3LA5_A | 0.76 | 0.59 | 1.00 | 20 | 2465 | 0 | 0 | 0 | 0 | 14 | |
| 3NPB_A | 0.30 | 0.24 | 0.39 | 11 | 6993 | 18 | 1 | 16 | 1 | 35 | |
| 3O58_2 | 0.76 | 0.76 | 0.76 | 29 | 7222 | 12 | 3 | 6 | 3 | 9 | |
| 3O58_3 | 0.00 | 0.00 | 0.00 | 0 | 12403 | 0 | 0 | 0 | 0 | 35 | |
| 3PDR_A | 0.00 | 0.00 | 0.00 | 0 | 12880 | 0 | 0 | 0 | 0 | 72 | |
| 3RKF_A | 0.70 | 0.50 | 1.00 | 17 | 2194 | 0 | 0 | 0 | 0 | 17 | |
| 3SD1_A | 0.61 | 0.50 | 0.75 | 21 | 3888 | 7 | 1 | 6 | 0 | 21 | |
| 3ZEX_D | 0.80 | 0.71 | 0.90 | 35 | 6982 | 4 | 0 | 4 | 0 | 14 | |
| 3ZEX_C | 0.00 | 0.00 | 0.00 | 0 | 14196 | 0 | 0 | 0 | 0 | 52 | |
| 3ZND_W | -0.01 | 0.00 | 0.00 | 0 | 2988 | 16 | 3 | 12 | 1 | 23 | |
| 4A1C_2 | 0.00 | 0.00 | 0.00 | 0 | 11781 | 0 | 0 | 0 | 0 | 33 | |
| 4A1C_3 | 0.70 | 0.59 | 0.84 | 32 | 7102 | 7 | 0 | 6 | 1 | 22 | |
| 4AOB_A | 0.39 | 0.26 | 0.58 | 11 | 4352 | 9 | 0 | 8 | 1 | 31 | |
| 4ENB_A | 0.39 | 0.16 | 1.00 | 3 | 1272 | 0 | 0 | 0 | 0 | 16 | |
| 4ENC_A | 0.51 | 0.26 | 1.00 | 5 | 1321 | 0 | 0 | 0 | 0 | 14 | |
| 4FRG_B | 0.00 | 0.00 | 0.00 | 0 | 3486 | 0 | 0 | 0 | 0 | 32 |
Matthews Correlation Coeffient, Sensitivity and Positive Predictive Value have been calculated based on the paper by Gardener & Giegerich, 2004.