CompaRNA - on-line benchmarks of RNA structure prediction methods
Home

Methods
Datasets
Rankings
RNA 2D Atlas

Help
FAQ

Contact us
RSS feeds
Twitter

Table of contents:

  1. Overview

  2. Performance Plots

  3. Performance of PETfold_pre2.0(seed) - scored higher in this pairwise comparison

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

  5. Compile and download dataset for PETfold_pre2.0(seed) & Murlet(seed) [.zip] - may take several seconds...


Overview

Metric PETfold_pre2.0(seed) Murlet(seed)
MCC 0.769 > 0.473
Average MCC ± 95% Confidence Intervals 0.744 ± 0.080 > 0.476 ± 0.126
Sensitivity 0.697 > 0.300
Positive Predictive Value 0.853 > 0.756
Total TP 209 > 90
Total TN 27880 < 28006
Total FP 81 > 34
Total FP CONTRA 13 > 2
Total FP INCONS 23 < 27
Total FP COMP 45 > 5
Total FN 91 < 210
P-value 1.87872347734e-08

^top




Performance plots


  1. Comparison of performance of PETfold_pre2.0(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 PETfold_pre2.0(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 PETfold_pre2.0(seed) and Murlet(seed)).

  3. Comparison of average Matthews Correlation Coefficients (MCCs) for PETfold_pre2.0(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 PETfold_pre2.0(seed) and Murlet(seed)).

^top





Performance of PETfold_pre2.0(seed) - scored higher in this pairwise comparison

1. Total counts & total scores for PETfold_pre2.0(seed)

Total Base Pair Counts
Total TP 209
Total TN 27880
Total FP 81
Total FP CONTRA 13
Total FP INCONS 23
Total FP COMP 45
Total FN 91
Total Scores
MCC 0.769
Average MCC ± 95% Confidence Intervals 0.744 ± 0.080
Sensitivity 0.697
Positive Predictive Value 0.853
Nr of predictions 13

^top



2. Individual counts for PETfold_pre2.0(seed) [ download as .csv ]

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
2LC8_A 0.41 0.33 0.55 6 517 5 0 5 0 12
3J3E_8 0.71 0.67 0.77 10 2729 8 1 2 5 5
3J3F_8 0.86 0.84 0.89 16 4743 13 2 0 11 3
3W1K_J 0.85 0.81 0.89 25 1650 4 2 1 1 6
3W3S_B 0.80 0.73 0.89 24 1962 6 1 2 3 9
3ZEX_C 0.70 0.59 0.85 17 5354 12 1 2 9 12
4A1C_2 0.79 0.75 0.83 15 4498 12 1 2 9 5
4AOB_A 0.85 0.79 0.92 23 1412 4 0 2 2 6
4ENB_A 0.61 0.53 0.73 8 461 5 1 2 2 7
4ENC_A 0.61 0.53 0.73 8 485 5 1 2 2 7
4FRG_B 0.87 0.83 0.91 20 1180 3 0 2 1 4
4FRN_A 0.83 0.79 0.88 22 1823 3 2 1 0 6
4JF2_A 0.76 0.63 0.94 15 1066 1 1 0 0 9

^top



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

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

Total Base Pair Counts
Total TP 90
Total TN 28006
Total FP 34
Total FP CONTRA 2
Total FP INCONS 27
Total FP COMP 5
Total FN 210
Total Scores
MCC 0.473
Average MCC ± 95% Confidence Intervals 0.476 ± 0.126
Sensitivity 0.300
Positive Predictive Value 0.756
Nr of predictions 13

^top



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 -0.03 0.00 0.00 0 516 12 0 12 0 18
3J3E_8 0.36 0.13 1.00 2 2740 2 0 0 2 13
3J3F_8 0.61 0.37 1.00 7 4754 0 0 0 0 12
3W1K_J 0.47 0.26 0.89 8 1669 1 0 1 0 23
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
4JF2_A 0.47 0.29 0.78 7 1073 4 1 1 2 17

^top


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