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Table of contents:
- Overview
- Performance Plots
- Performance of MCFold - scored higher in this pairwise comparison
- Performance of RSpredict(seed) - scored lower in this pairwise comparison
- Compile and download dataset for MCFold & RSpredict(seed) [.zip] - may take several seconds...
Overview
| Metric | MCFold | RSpredict(seed) | |
|---|---|---|---|
| MCC | 0.602 | > | 0.415 |
| Average MCC ± 95% Confidence Intervals | 0.614 ± 0.097 | > | 0.333 ± 0.120 |
| Sensitivity | 0.650 | > | 0.261 |
| Positive Predictive Value | 0.568 | < | 0.674 |
| Total TP | 540 | > | 217 |
| Total TN | 55919 | < | 56547 |
| Total FP | 519 | > | 118 |
| Total FP CONTRA | 123 | > | 13 |
| Total FP INCONS | 287 | > | 92 |
| Total FP COMP | 109 | > | 13 |
| Total FN | 291 | < | 614 |
| P-value | 3.56938820447e-08 | ||
Performance plots
-
Comparison of performance of MCFold 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 MCFold and RSpredict(seed)).
-
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 MCFold and RSpredict(seed)).
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Comparison of average Matthews Correlation Coefficients (MCCs) for MCFold 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 MCFold and RSpredict(seed)).
Performance of MCFold - scored higher in this pairwise comparison
1. Total counts & total scores for MCFold
| Total Base Pair Counts | |
|---|---|
| Total TP | 540 |
| Total TN | 55919 |
| Total FP | 519 |
| Total FP CONTRA | 123 |
| Total FP INCONS | 287 |
| Total FP COMP | 109 |
| Total FN | 291 |
| Total Scores | |
|---|---|
| MCC | 0.602 |
| Average MCC ± 95% Confidence Intervals | 0.614 ± 0.097 |
| Sensitivity | 0.650 |
| Positive Predictive Value | 0.568 |
| Nr of predictions | 38 |
2. Individual counts for MCFold [ download as .csv ]
| RNA Chain | Rfam family | MCC | SENS | PPV | TP | TN | FP | FP CONTRA | FP INCONS | FP COMP | FN |
| 2KDQ_B | 1.00 | 1.00 | 1.00 | 10 | 164 | 1 | 0 | 0 | 1 | 0 | |
| 2KE6_A | 1.00 | 1.00 | 1.00 | 18 | 449 | 1 | 0 | 0 | 1 | 0 | |
| 2KUR_A | 1.00 | 1.00 | 1.00 | 19 | 448 | 0 | 0 | 0 | 0 | 0 | |
| 2KUU_A | 1.00 | 1.00 | 1.00 | 18 | 429 | 1 | 0 | 0 | 1 | 0 | |
| 2KUV_A | 1.00 | 1.00 | 1.00 | 19 | 420 | 0 | 0 | 0 | 0 | 0 | |
| 2KUW_A | 1.00 | 1.00 | 1.00 | 18 | 452 | 1 | 0 | 0 | 1 | 0 | |
| 2KX8_A | 1.00 | 1.00 | 1.00 | 16 | 355 | 0 | 0 | 0 | 0 | 0 | |
| 2L1F_A | 0.79 | 0.78 | 0.82 | 18 | 741 | 4 | 0 | 4 | 0 | 5 | |
| 2L1F_B | 0.80 | 0.79 | 0.83 | 19 | 768 | 4 | 0 | 4 | 0 | 5 | |
| 2L94_A | 1.00 | 1.00 | 1.00 | 18 | 339 | 1 | 0 | 0 | 1 | 0 | |
| 2LC8_A | 0.44 | 0.44 | 0.47 | 8 | 511 | 10 | 0 | 9 | 1 | 10 | |
| 2WRQ_Y | 0.38 | 0.56 | 0.26 | 5 | 1133 | 21 | 8 | 6 | 7 | 4 | |
| 2WWQ_V | 0.19 | 0.21 | 0.19 | 4 | 1183 | 20 | 3 | 14 | 3 | 15 | |
| 2XKV_B | 0.20 | 0.27 | 0.16 | 3 | 1816 | 30 | 4 | 12 | 14 | 8 | |
| 2XQD_Y | 0.39 | 0.43 | 0.38 | 9 | 1105 | 18 | 2 | 13 | 3 | 12 | |
| 2XXA_G | 0.23 | 0.26 | 0.24 | 9 | 2007 | 30 | 1 | 28 | 1 | 26 | |
| 2ZZN_D | 0.69 | 0.73 | 0.67 | 16 | 960 | 11 | 1 | 7 | 3 | 6 | |
| 3A2K_C | 0.49 | 0.55 | 0.46 | 12 | 1082 | 14 | 3 | 11 | 0 | 10 | |
| 3A3A_A | 0.98 | 0.97 | 1.00 | 29 | 1471 | 0 | 0 | 0 | 0 | 1 | |
| 3AKZ_H | 0.46 | 0.50 | 0.43 | 10 | 1104 | 16 | 5 | 8 | 3 | 10 | |
| 3AMU_B | 0.50 | 0.58 | 0.44 | 11 | 1132 | 15 | 4 | 10 | 1 | 8 | |
| 3GX2_A | 0.58 | 0.61 | 0.57 | 17 | 1419 | 15 | 1 | 12 | 2 | 11 | |
| 3IVN_B | 0.45 | 0.48 | 0.46 | 11 | 879 | 14 | 5 | 8 | 1 | 12 | |
| 3IZF_C | 0.92 | 0.94 | 0.89 | 33 | 2603 | 10 | 0 | 4 | 6 | 2 | |
| 3J16_L | 0.54 | 0.57 | 0.52 | 12 | 1136 | 12 | 4 | 7 | 1 | 9 | |
| 3JYV_7 | 0.25 | 0.30 | 0.24 | 6 | 1086 | 20 | 8 | 11 | 1 | 14 | |
| 3JYX_3 | 0.46 | 0.67 | 0.32 | 10 | 2347 | 28 | 15 | 6 | 7 | 5 | |
| 3JYX_4 | 0.36 | 0.58 | 0.23 | 7 | 4725 | 37 | 19 | 5 | 13 | 5 | |
| 3LA5_A | 0.44 | 0.44 | 0.48 | 11 | 931 | 12 | 2 | 10 | 0 | 14 | |
| 3O58_2 | 0.25 | 0.29 | 0.23 | 9 | 2715 | 31 | 6 | 24 | 1 | 22 | |
| 3O58_3 | 0.28 | 0.36 | 0.22 | 8 | 4727 | 39 | 14 | 15 | 10 | 14 | |
| 3PDR_A | 0.78 | 0.80 | 0.77 | 40 | 4788 | 14 | 5 | 7 | 2 | 10 | |
| 3RKF_A | 0.89 | 0.88 | 0.91 | 21 | 843 | 3 | 0 | 2 | 1 | 3 | |
| 3SD1_A | 0.43 | 0.45 | 0.43 | 13 | 1503 | 17 | 1 | 16 | 0 | 16 | |
| 4A1C_2 | 0.18 | 0.25 | 0.14 | 5 | 4480 | 45 | 12 | 19 | 14 | 15 | |
| 4A1C_3 | 0.86 | 0.86 | 0.86 | 32 | 2726 | 9 | 0 | 5 | 4 | 5 | |
| 4ENB_A | 0.78 | 0.73 | 0.85 | 11 | 459 | 4 | 0 | 2 | 2 | 4 | |
| 4ENC_A | 0.34 | 0.33 | 0.38 | 5 | 483 | 11 | 0 | 8 | 3 | 10 |
Performance of RSpredict(seed) - scored lower in this pairwise comparison
1. Total counts & total scores for RSpredict(seed)
| Total Base Pair Counts | |
|---|---|
| Total TP | 217 |
| Total TN | 56547 |
| Total FP | 118 |
| Total FP CONTRA | 13 |
| Total FP INCONS | 92 |
| Total FP COMP | 13 |
| Total FN | 614 |
| Total Scores | |
|---|---|
| MCC | 0.415 |
| Average MCC ± 95% Confidence Intervals | 0.333 ± 0.120 |
| Sensitivity | 0.261 |
| Positive Predictive Value | 0.674 |
| Nr of predictions | 38 |
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 |
| 2KDQ_B | 0.89 | 0.80 | 1.00 | 8 | 166 | 0 | 0 | 0 | 0 | 2 | |
| 2KE6_A | 0.85 | 0.78 | 0.93 | 14 | 452 | 2 | 0 | 1 | 1 | 4 | |
| 2KUR_A | 0.86 | 0.79 | 0.94 | 15 | 451 | 1 | 0 | 1 | 0 | 4 | |
| 2KUU_A | 0.85 | 0.78 | 0.93 | 14 | 432 | 2 | 0 | 1 | 1 | 4 | |
| 2KUV_A | 0.85 | 0.79 | 0.94 | 15 | 423 | 1 | 0 | 1 | 0 | 4 | |
| 2KUW_A | 0.75 | 0.67 | 0.86 | 12 | 456 | 3 | 0 | 2 | 1 | 6 | |
| 2KX8_A | -0.01 | 0.00 | 0.00 | 0 | 370 | 1 | 0 | 1 | 0 | 16 | |
| 2L1F_A | 0.81 | 0.78 | 0.86 | 18 | 742 | 3 | 0 | 3 | 0 | 5 | |
| 2L1F_B | 0.87 | 0.83 | 0.91 | 20 | 769 | 2 | 0 | 2 | 0 | 4 | |
| 2L94_A | 0.55 | 0.50 | 0.64 | 9 | 343 | 6 | 0 | 5 | 1 | 9 | |
| 2LC8_A | -0.03 | 0.00 | 0.00 | 0 | 515 | 13 | 0 | 13 | 0 | 18 | |
| 2WRQ_Y | 0.00 | 0.00 | 0.00 | 0 | 1150 | 3 | 1 | 1 | 1 | 9 | |
| 2WWQ_V | -0.01 | 0.00 | 0.00 | 0 | 1199 | 6 | 0 | 5 | 1 | 19 | |
| 2XKV_B | 0.38 | 0.36 | 0.40 | 4 | 1825 | 8 | 4 | 2 | 2 | 7 | |
| 2XQD_Y | -0.01 | 0.00 | 0.00 | 0 | 1124 | 5 | 0 | 5 | 0 | 21 | |
| 2XXA_G | 0.37 | 0.20 | 0.70 | 7 | 2035 | 3 | 0 | 3 | 0 | 28 | |
| 2ZZN_D | 0.38 | 0.18 | 0.80 | 4 | 979 | 1 | 1 | 0 | 0 | 18 | |
| 3A2K_C | -0.01 | 0.00 | 0.00 | 0 | 1106 | 2 | 0 | 2 | 0 | 22 | |
| 3A3A_A | 0.53 | 0.37 | 0.79 | 11 | 1486 | 3 | 0 | 3 | 0 | 19 | |
| 3AKZ_H | -0.01 | 0.00 | 0.00 | 0 | 1125 | 2 | 0 | 2 | 0 | 20 | |
| 3AMU_B | -0.01 | 0.00 | 0.00 | 0 | 1155 | 2 | 0 | 2 | 0 | 19 | |
| 3GX2_A | 0.42 | 0.21 | 0.86 | 6 | 1442 | 1 | 0 | 1 | 0 | 22 | |
| 3IVN_B | 0.81 | 0.70 | 0.94 | 16 | 886 | 1 | 1 | 0 | 0 | 7 | |
| 3IZF_C | 0.00 | 0.00 | 0.00 | 0 | 2635 | 5 | 0 | 5 | 0 | 35 | |
| 3J16_L | 0.00 | 0.00 | 0.00 | 0 | 1158 | 1 | 0 | 1 | 0 | 21 | |
| 3JYV_7 | -0.01 | 0.00 | 0.00 | 0 | 1108 | 4 | 0 | 3 | 1 | 20 | |
| 3JYX_3 | 0.00 | 0.00 | 0.00 | 0 | 2373 | 5 | 1 | 4 | 0 | 15 | |
| 3JYX_4 | 0.00 | 0.00 | 0.00 | 0 | 4754 | 5 | 0 | 2 | 3 | 12 | |
| 3LA5_A | 0.82 | 0.68 | 1.00 | 17 | 937 | 0 | 0 | 0 | 0 | 8 | |
| 3O58_2 | 0.00 | 0.00 | 0.00 | 0 | 2751 | 3 | 0 | 3 | 0 | 31 | |
| 3O58_3 | 0.28 | 0.14 | 0.60 | 3 | 4759 | 2 | 0 | 2 | 0 | 19 | |
| 3PDR_A | 0.00 | 0.00 | 0.00 | 0 | 4832 | 8 | 0 | 8 | 0 | 50 | |
| 3RKF_A | 0.84 | 0.75 | 0.95 | 18 | 847 | 1 | 1 | 0 | 0 | 6 | |
| 3SD1_A | 0.00 | 0.00 | 0.00 | 0 | 1533 | 0 | 0 | 0 | 0 | 29 | |
| 4A1C_2 | 0.00 | 0.00 | 0.00 | 0 | 4512 | 5 | 2 | 2 | 1 | 20 | |
| 4A1C_3 | 0.00 | 0.00 | 0.00 | 0 | 2759 | 4 | 2 | 2 | 0 | 37 | |
| 4ENB_A | 0.34 | 0.20 | 0.60 | 3 | 467 | 2 | 0 | 2 | 0 | 12 | |
| 4ENC_A | 0.34 | 0.20 | 0.60 | 3 | 491 | 2 | 0 | 2 | 0 | 12 |
Matthews Correlation Coeffient, Sensitivity and Positive Predictive Value have been calculated based on the paper by Gardener & Giegerich, 2004.