Create ROC plot
Create a receiver operating characteristic (ROC) plot at various threshold settings.
Anaquin dataset created by
Reference ratio groups
Label of the plot. Default to
Title of the legend. Default to
Reserved for internal testing
plotROC requires the following data inputs from
| ||List of sequin identifiers (eg. R2_11_2)|
| ||Classified labels ('TP' or 'FP')|
| ||How the ROC points should be ranked|
| ||Expected ratio; eg: expected log-fold ratio|
Create a receiver operating characteristic (ROC) plot at various threshold settings. The true positive rate (TPR) is plotted on the x-axis and false positive rate (FPR) is plotted on the y-axis.
The function requires a scoring threshold function, and illustrates the performance of the data as the threshold is varied. Common scoring threshold include p-value, sequencing depth and allele frequency, etc.
ROC plot is a useful diagnostic performance tool; it provides tools to select possibly optimal models and to discard suboptimal ones. In particularly, the AUC statistics indicate the performance of the model relatively to a random experiment (AUC 0.5).
The functions does not return anything but it prints a ROC plot and it's AUC statistics.
Ted Wong firstname.lastname@example.org
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library(Anaquin) # # Data set generated by DESeq2 and Anaquin. described in Section 22.214.171.124 of # the user guide. # data(UserGuideData_5.6.3) # Sequin names seqs <- row.names(UserGuideData_5.6.3) # Expected log-fold ratio <- UserGuideData_5.6.3$ExpLFC # How the ROC curves are ranked score <- 1-UserGuideData_5.6.3$Pval # Classified labels (TP/FP) label <- UserGuideData_5.6.3$Label anaquin <- AnaquinData(analysis='PlotROC', seqs=seqs, ratio=ratio, score=score, label=label) plotROC(anaquin, title='ROC Plot', refRats=0)
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