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Table of contents:

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric CentroidAlifold(seed) Murlet(seed)
MCC 0.702 > 0.474
Average MCC ± 95% Confidence Intervals 0.649 ± 0.116 > 0.468 ± 0.089
Sensitivity 0.508 > 0.270
Positive Predictive Value 0.972 > 0.838
Total TP 273 > 145
Total TN 83546 < 83654
Total FP 18 < 32
Total FP CONTRA 2 < 5
Total FP INCONS 6 < 23
Total FP COMP 10 > 4
Total FN 264 < 392
P-value 3.02344513449e-08

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Performance plots


  1. Comparison of performance of CentroidAlifold(seed) 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 CentroidAlifold(seed) 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 CentroidAlifold(seed) and Murlet(seed)).

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

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

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

Total Base Pair Counts
Total TP 273
Total TN 83546
Total FP 18
Total FP CONTRA 2
Total FP INCONS 6
Total FP COMP 10
Total FN 264
Total Scores
MCC 0.702
Average MCC ± 95% Confidence Intervals 0.649 ± 0.116
Sensitivity 0.508
Positive Predictive Value 0.972
Nr of predictions 15

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

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
2LC8_A 0.00 0.00 0.00 0 1540 0 0 0 0 20
3A3A_A 0.85 0.73 1.00 27 3628 0 0 0 0 10
3GX2_A 0.77 0.60 1.00 24 4347 1 0 0 1 16
3IVN_B 0.78 0.65 0.95 20 2325 1 1 0 0 11
3JYX_4 0.52 0.30 0.91 10 12235 3 0 1 2 23
3LA5_A 0.78 0.62 1.00 21 2464 0 0 0 0 13
3NPB_A 0.71 0.54 0.93 25 6994 4 1 1 2 21
3O58_3 0.56 0.34 0.92 12 12390 1 0 1 0 23
3PDR_A 0.77 0.61 0.98 44 12835 3 0 1 2 28
3RKF_A 0.76 0.59 1.00 20 2191 0 0 0 0 14
3SD1_A 0.71 0.52 0.96 22 3893 1 0 1 0 20
4A1C_2 0.46 0.24 0.89 8 11772 3 0 1 2 25
4AOB_A 0.75 0.57 1.00 24 4347 1 0 0 1 18
4ENB_A 0.65 0.42 1.00 8 1267 0 0 0 0 11
4ENC_A 0.65 0.42 1.00 8 1318 0 0 0 0 11

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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 145
Total TN 83654
Total FP 32
Total FP CONTRA 5
Total FP INCONS 23
Total FP COMP 4
Total FN 392
Total Scores
MCC 0.474
Average MCC ± 95% Confidence Intervals 0.468 ± 0.089
Sensitivity 0.270
Positive Predictive Value 0.838
Nr of predictions 15

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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
2LC8_A -0.01 0.00 0.00 0 1528 12 0 12 0 20
3A3A_A 0.57 0.32 1.00 12 3643 0 0 0 0 25
3GX2_A 0.59 0.35 1.00 14 4357 1 0 0 1 26
3IVN_B 0.53 0.39 0.75 12 2330 4 2 2 0 19
3JYX_4 0.23 0.09 0.60 3 12241 4 0 2 2 30
3LA5_A 0.58 0.41 0.82 14 2468 3 1 2 0 20
3NPB_A 0.49 0.28 0.87 13 7006 2 1 1 0 33
3O58_3 0.45 0.20 1.00 7 12396 0 0 0 0 28
3PDR_A 0.44 0.19 1.00 14 12866 0 0 0 0 58
3RKF_A 0.53 0.35 0.80 12 2196 3 1 2 0 22
3SD1_A 0.47 0.26 0.85 11 3903 2 0 2 0 31
4A1C_2 0.46 0.21 1.00 7 11774 0 0 0 0 26
4AOB_A 0.58 0.33 1.00 14 4357 1 0 0 1 28
4ENB_A 0.56 0.32 1.00 6 1269 0 0 0 0 13
4ENC_A 0.56 0.32 1.00 6 1320 0 0 0 0 13

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