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

  1. Overview

  2. Performance Plots

  3. Performance of RNAshapes - scored higher in this pairwise comparison

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

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


Overview

Metric RNAshapes Murlet(seed)
MCC 0.746 > 0.594
Average MCC ± 95% Confidence Intervals 0.763 ± 0.091 > 0.592 ± 0.069
Sensitivity 0.750 > 0.418
Positive Predictive Value 0.749 < 0.855
Total TP 528 > 294
Total TN 49255 < 49616
Total FP 278 > 63
Total FP CONTRA 51 > 5
Total FP INCONS 126 > 45
Total FP COMP 101 > 13
Total FN 176 < 410
P-value 3.56938820447e-08

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Performance plots


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

  2. Comparison of performance of RNAshapes 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 RNAshapes and Murlet(seed)).

  3. 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 RNAshapes and Murlet(seed)).

  4. 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 RNAshapes and Murlet(seed)).

  5. Comparison of average Matthews Correlation Coefficients (MCCs) for RNAshapes 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 RNAshapes and Murlet(seed)).

  6. Comparison of average Matthews Correlation Coefficients (MCCs) for RNAshapes 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 RNAshapes and Murlet(seed)).

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Performance of RNAshapes - scored higher in this pairwise comparison

1. Total counts & total scores for RNAshapes

Total Base Pair Counts
Total TP 528
Total TN 49255
Total FP 278
Total FP CONTRA 51
Total FP INCONS 126
Total FP COMP 101
Total FN 176
Total Scores
MCC 0.746
Average MCC ± 95% Confidence Intervals 0.763 ± 0.091
Sensitivity 0.750
Positive Predictive Value 0.749
Nr of predictions 30

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2. Individual counts for RNAshapes [ 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 0 0 0 0 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
2L1F_A 0.89 0.87 0.91 20 741 2 0 2 0 3
2L1F_B 0.98 0.96 1.00 23 768 0 0 0 0 1
2L94_A 1.00 1.00 1.00 18 339 1 0 0 1 0
2LC8_A 0.64 0.61 0.69 11 512 5 0 5 0 7
2XKV_B 0.64 0.73 0.57 8 1821 24 0 6 18 3
2XXA_G 1.00 1.00 1.00 35 2010 1 0 0 1 0
3A3A_A 0.84 0.80 0.89 24 1473 3 0 3 0 6
3GX2_A 0.91 0.89 0.93 25 1422 3 1 1 1 3
3IVN_B 0.91 0.83 1.00 19 884 0 0 0 0 4
3JYX_4 0.61 0.83 0.45 10 4734 35 10 2 23 2
3LA5_A 0.89 0.80 1.00 20 934 0 0 0 0 5
3NPB_A 0.84 0.76 0.93 28 2248 5 1 1 3 9
3O58_3 0.41 0.50 0.34 11 4732 38 6 15 17 11
3PDR_A 0.80 0.80 0.80 40 4790 12 3 7 2 10
3RKF_A 0.91 0.83 1.00 20 846 0 0 0 0 4
3SD1_A 0.77 0.76 0.79 22 1505 6 4 2 0 7
3W3S_B 0.60 0.58 0.63 19 1959 12 2 9 1 14
3ZEX_C 0.29 0.34 0.26 10 5335 42 5 24 13 19
4A1C_2 0.19 0.25 0.16 5 4484 41 11 16 14 15
4AOB_A 0.60 0.59 0.63 17 1410 11 4 6 1 12
4ENB_A 0.85 0.73 1.00 11 461 2 0 0 2 4
4ENC_A 0.37 0.33 0.45 5 485 7 0 6 1 10
4FRG_B 0.36 0.38 0.38 9 1178 15 2 13 0 15
4FRN_A 0.59 0.57 0.62 16 1822 10 2 8 0 12

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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 294
Total TN 49616
Total FP 63
Total FP CONTRA 5
Total FP INCONS 45
Total FP COMP 13
Total FN 410
Total Scores
MCC 0.594
Average MCC ± 95% Confidence Intervals 0.592 ± 0.069
Sensitivity 0.418
Positive Predictive Value 0.855
Nr of predictions 30

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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
2KDQ_B 0.54 0.30 1.00 3 171 0 0 0 0 7
2KE6_A 0.67 0.56 0.83 10 455 2 0 2 0 8
2KUR_A 0.65 0.53 0.83 10 455 2 0 2 0 9
2KUU_A 0.67 0.56 0.83 10 435 2 0 2 0 8
2KUV_A 0.91 0.84 1.00 16 423 0 0 0 0 3
2KUW_A 0.88 0.83 0.94 15 454 2 0 1 1 3
2L1F_A 0.83 0.78 0.90 18 743 2 0 2 0 5
2L1F_B 0.82 0.75 0.90 18 771 2 0 2 0 6
2L94_A 0.57 0.39 0.88 7 349 2 0 1 1 11
2LC8_A -0.03 0.00 0.00 0 516 12 0 12 0 18
2XKV_B 0.60 0.36 1.00 4 1831 2 0 0 2 7
2XXA_G 0.41 0.17 1.00 6 2039 0 0 0 0 29
3A3A_A 0.63 0.40 1.00 12 1488 0 0 0 0 18
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
3JYX_4 0.50 0.25 1.00 3 4753 4 0 0 4 9
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
3W3S_B 0.45 0.27 0.75 9 1977 3 0 3 0 24
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
4FRN_A 0.66 0.50 0.88 14 1832 2 1 1 0 14

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