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Table of contents:

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric MXScarna(seed) Murlet(seed)
MCC 0.735 > 0.594
Average MCC ± 95% Confidence Intervals 0.718 ± 0.081 > 0.592 ± 0.069
Sensitivity 0.689 > 0.418
Positive Predictive Value 0.792 < 0.855
Total TP 485 > 294
Total TN 49348 < 49616
Total FP 220 > 63
Total FP CONTRA 41 > 5
Total FP INCONS 86 > 45
Total FP COMP 93 > 13
Total FN 219 < 410
P-value 3.56938820447e-08

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Performance plots


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

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

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

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

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

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

Total Base Pair Counts
Total TP 485
Total TN 49348
Total FP 220
Total FP CONTRA 41
Total FP INCONS 86
Total FP COMP 93
Total FN 219
Total Scores
MCC 0.735
Average MCC ± 95% Confidence Intervals 0.718 ± 0.081
Sensitivity 0.689
Positive Predictive Value 0.792
Nr of predictions 30

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2. Individual counts for MXScarna(seed) [ 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 0.91 0.89 0.94 16 450 2 0 1 1 2
2KUR_A 0.92 0.89 0.94 17 449 1 0 1 0 2
2KUU_A 0.91 0.89 0.94 16 430 2 0 1 1 2
2KUV_A 0.92 0.89 0.94 17 421 1 0 1 0 2
2KUW_A 0.78 0.72 0.87 13 455 3 0 2 1 5
2L1F_A 0.93 0.91 0.95 21 741 1 0 1 0 2
2L1F_B 0.98 0.96 1.00 23 768 0 0 0 0 1
2L94_A 0.55 0.56 0.59 10 340 8 0 7 1 8
2LC8_A -0.03 0.00 0.00 0 518 12 0 10 2 18
2XKV_B 0.78 0.82 0.75 9 1823 20 0 3 17 2
2XXA_G 0.74 0.69 0.80 24 2015 7 0 6 1 11
3A3A_A 0.84 0.77 0.92 23 1475 4 0 2 2 7
3GX2_A 0.83 0.82 0.85 23 1422 7 2 2 3 5
3IVN_B 0.69 0.57 0.87 13 888 2 2 0 0 10
3JYX_4 0.70 0.83 0.59 10 4739 21 6 1 14 2
3LA5_A 0.82 0.72 0.95 18 935 1 1 0 0 7
3NPB_A 0.76 0.70 0.84 26 2247 10 2 3 5 11
3O58_3 0.54 0.50 0.58 11 4745 20 5 3 12 11
3PDR_A 0.87 0.88 0.86 44 4789 10 4 3 3 6
3RKF_A 0.86 0.75 1.00 18 848 0 0 0 0 6
3SD1_A 0.74 0.76 0.73 22 1503 9 4 4 1 7
3W3S_B 0.74 0.70 0.79 23 1960 7 0 6 1 10
3ZEX_C 0.39 0.31 0.50 9 5356 21 3 6 12 20
4A1C_2 0.45 0.40 0.50 8 4500 20 4 4 12 12
4AOB_A 0.71 0.69 0.74 20 1410 10 2 5 3 9
4ENB_A 0.54 0.40 0.75 6 464 2 0 2 0 9
4ENC_A 0.48 0.40 0.60 6 486 4 1 3 0 9
4FRG_B 0.49 0.42 0.59 10 1185 8 2 5 1 14
4FRN_A 0.70 0.68 0.73 19 1822 7 3 4 0 9

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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.