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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 0.791 > 0.584
Average MCC ± 95% Confidence Intervals 0.671 ± 0.054 > 0.476 ± 0.098
Sensitivity 0.737 > 0.492
Positive Predictive Value 0.849 > 0.694
Total TP 530 > 354
Total TN 1014995 < 1015109
Total FP 132 < 180
Total FP CONTRA 31 > 6
Total FP INCONS 63 < 150
Total FP COMP 38 > 24
Total FN 189 < 365
P-value 1.26497248087e-08

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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)).

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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 530
Total TN 1014995
Total FP 132
Total FP CONTRA 31
Total FP INCONS 63
Total FP COMP 38
Total FN 189
Total Scores
MCC 0.791
Average MCC ± 95% Confidence Intervals 0.671 ± 0.054
Sensitivity 0.737
Positive Predictive Value 0.849
Nr of predictions 14

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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
CRW_01343 0.87 0.85 0.89 367 977489 81 8 37 36 67
PDB_00005 0.80 0.64 1.00 9 937 0 0 0 0 5
PDB_00716 0.68 0.57 0.81 13 2685 3 0 3 0 10
PDB_01092 0.68 0.56 0.83 29 10118 8 0 6 2 23
RFA_00632 0.69 0.64 0.75 18 4071 6 2 4 0 10
RFA_00636 0.73 0.68 0.79 19 3981 5 2 3 0 9
RFA_00767 0.63 0.56 0.71 10 1877 4 3 1 0 8
RFA_00768 0.63 0.56 0.71 10 1877 4 3 1 0 8
RFA_00769 0.63 0.56 0.71 10 1939 4 3 1 0 8
RFA_00770 0.63 0.56 0.71 10 2002 4 3 1 0 8
RFA_00773 0.63 0.56 0.71 10 1939 4 3 1 0 8
RFA_00779 0.63 0.56 0.71 10 1939 4 3 1 0 8
RFA_00808 0.71 0.56 0.90 9 2006 1 1 0 0 7
RFA_00809 0.47 0.38 0.60 6 2135 4 0 4 0 10

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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 354
Total TN 1015109
Total FP 180
Total FP CONTRA 6
Total FP INCONS 150
Total FP COMP 24
Total FN 365
Total Scores
MCC 0.584
Average MCC ± 95% Confidence Intervals 0.476 ± 0.098
Sensitivity 0.492
Positive Predictive Value 0.694
Nr of predictions 14

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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
CRW_01343 0.64 0.61 0.68 263 977515 145 6 117 22 171
PDB_00005 0.53 0.29 1.00 4 942 2 0 0 2 10
PDB_00716 0.23 0.13 0.43 3 2694 4 0 4 0 20
PDB_01092 0.69 0.48 1.00 25 10128 0 0 0 0 27
RFA_00632 0.21 0.11 0.43 3 4088 4 0 4 0 25
RFA_00636 0.21 0.11 0.43 3 3998 4 0 4 0 25
RFA_00767 0.47 0.33 0.67 6 1882 3 0 3 0 12
RFA_00768 0.41 0.28 0.63 5 1883 3 0 3 0 13
RFA_00769 0.57 0.44 0.73 8 1942 3 0 3 0 10
RFA_00770 0.57 0.44 0.73 8 2005 3 0 3 0 10
RFA_00773 0.41 0.28 0.63 5 1945 3 0 3 0 13
RFA_00779 0.47 0.33 0.67 6 1944 3 0 3 0 12
RFA_00808 0.75 0.56 1.00 9 2007 0 0 0 0 7
RFA_00809 0.50 0.38 0.67 6 2136 3 0 3 0 10

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