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

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric Multilign(seed) RSpredict(seed)
MCC 0.485 > 0.479
Average MCC ± 95% Confidence Intervals 0.399 ± 0.173 < 0.495 ± 0.104
Sensitivity 0.386 < 0.423
Positive Predictive Value 0.619 > 0.552
Total TP 83 < 91
Total TN 22737 > 22706
Total FP 52 < 80
Total FP CONTRA 6 < 28
Total FP INCONS 45 < 46
Total FP COMP 1 < 6
Total FN 132 > 124
P-value 0.0114155930811

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Performance plots


  1. Comparison of performance of Multilign(seed) 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 Multilign(seed) and RSpredict(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 Multilign(seed) and RSpredict(seed)).

  3. Comparison of average Matthews Correlation Coefficients (MCCs) for Multilign(seed) 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 Multilign(seed) and RSpredict(seed)).

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

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

Total Base Pair Counts
Total TP 83
Total TN 22737
Total FP 52
Total FP CONTRA 6
Total FP INCONS 45
Total FP COMP 1
Total FN 132
Total Scores
MCC 0.485
Average MCC ± 95% Confidence Intervals 0.399 ± 0.173
Sensitivity 0.386
Positive Predictive Value 0.619
Nr of predictions 13

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

RNA Chain Rfam family MCC SENS PPV TP TN FP FP CONTRA FP INCONS FP COMP FN
RFA_00416 0.57 0.53 0.62 8 1472 6 1 4 1 7
RFA_00654 0.00 0.00 0.00 0 2414 1 0 1 0 18
RFA_00658 0.00 0.00 0.00 0 1128 0 0 0 0 14
RFA_00664 0.00 0.00 0.00 0 990 0 0 0 0 14
RFA_00708 0.00 0.00 0.00 0 1035 0 0 0 0 14
RFA_00767 0.63 0.56 0.71 10 1877 4 0 4 0 8
RFA_00768 0.61 0.56 0.67 10 1876 5 0 5 0 8
RFA_00769 0.55 0.56 0.56 10 1935 8 3 5 0 8
RFA_00770 0.68 0.56 0.83 10 2004 2 0 2 0 8
RFA_00773 0.59 0.56 0.63 10 1937 6 1 5 0 8
RFA_00779 0.61 0.56 0.67 10 1938 5 0 5 0 8
RFA_00808 0.60 0.56 0.64 9 2002 5 0 5 0 7
RFA_00809 0.37 0.38 0.38 6 2129 10 1 9 0 10

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

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

Total Base Pair Counts
Total TP 91
Total TN 22706
Total FP 80
Total FP CONTRA 28
Total FP INCONS 46
Total FP COMP 6
Total FN 124
Total Scores
MCC 0.479
Average MCC ± 95% Confidence Intervals 0.495 ± 0.104
Sensitivity 0.423
Positive Predictive Value 0.552
Nr of predictions 13

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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
RFA_00416 0.63 0.40 1.00 6 1479 1 0 0 1 9
RFA_00654 0.35 0.28 0.45 5 2404 6 0 6 0 13
RFA_00658 0.64 0.57 0.73 8 1117 4 0 3 1 6
RFA_00664 0.59 0.50 0.70 7 980 4 0 3 1 7
RFA_00708 0.75 0.57 1.00 8 1027 1 0 0 1 6
RFA_00767 0.19 0.17 0.23 3 1878 10 3 7 0 15
RFA_00768 0.19 0.17 0.23 3 1878 10 3 7 0 15
RFA_00769 0.59 0.56 0.63 10 1937 6 4 2 0 8
RFA_00770 0.54 0.56 0.53 10 1997 9 6 3 0 8
RFA_00773 0.50 0.50 0.50 9 1935 9 6 3 0 9
RFA_00779 0.50 0.50 0.50 9 1935 9 6 3 0 9
RFA_00808 0.60 0.50 0.73 8 2005 4 0 3 1 8
RFA_00809 0.37 0.31 0.45 5 2134 7 0 6 1 11

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