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Table of contents:

  1. Overview

  2. Performance Plots

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

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

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


Overview

Metric Murlet(seed) RSpredict(seed)
MCC 0.584 > 0.510
Average MCC ± 95% Confidence Intervals 0.476 ± 0.098 < 0.490 ± 0.087
Sensitivity 0.492 > 0.414
Positive Predictive Value 0.694 > 0.627
Total TP 354 > 298
Total TN 1015109 < 1015144
Total FP 180 < 191
Total FP CONTRA 6 < 47
Total FP INCONS 150 > 130
Total FP COMP 24 > 14
Total FN 365 < 421
P-value 3.2348692827e-08

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Performance plots


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

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

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

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

Total Base Pair Counts
Total TP 298
Total TN 1015144
Total FP 191
Total FP CONTRA 47
Total FP INCONS 130
Total FP COMP 14
Total FN 421
Total Scores
MCC 0.510
Average MCC ± 95% Confidence Intervals 0.490 ± 0.087
Sensitivity 0.414
Positive Predictive Value 0.627
Nr of predictions 14

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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
CRW_01343 0.52 0.41 0.68 177 977639 95 12 73 10 257
PDB_00005 0.71 0.57 0.89 8 937 1 0 1 0 6
PDB_00716 0.59 0.48 0.73 11 2686 4 0 4 0 12
PDB_01092 0.48 0.37 0.63 19 10123 13 1 10 2 33
RFA_00632 0.47 0.39 0.58 11 4076 8 3 5 0 17
RFA_00636 0.62 0.54 0.71 15 3984 6 3 3 0 13
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.