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# README | ||
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### v0.1 It barely works | ||
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Initial release, includes 3 functions: | ||
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* **PPV_heatmap.R**: Plot PPV heatmaps | ||
* **PPV_diagnostic_vs_screening.R**: Plot PPV for a diagnostic and a screening group | ||
* **min_possible_prevalence.R**: Show minimum possible prevalence given the test characteristics |
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.createPPVmatrix <- function(Max_Prevalence, Sensitivity, Max_FP) { | ||
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# Libraries --------------------------------------------------------------- | ||
# if (!require('dplyr')) install.packages('dplyr'); library('dplyr') | ||
if (!require('reshape2')) install.packages('reshape2'); library('reshape2') | ||
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# DEBUG ------------------------------------------------------------------- | ||
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# Max_Prevalence = 4 | ||
# Sensitivity = 90 | ||
# Max_FP = 10 | ||
# PPV_NPV = "PPV" # NPV/PPV | ||
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#TEST Parameters ************** | ||
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# False Positives (x axis) | ||
Steps_FP <<- 100 | ||
Step_size_FP <<- Max_FP/Steps_FP | ||
Min_FP <<- 0 | ||
FP = seq(Min_FP, Max_FP, Step_size_FP) #With (Max_FP-Step_size_FP) we get 100 FPs. If we use Max_FP instead we have 101 (because we start at 0!) | ||
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#CONDITION Parameters *********** | ||
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#Prevalence_y - x out of y | ||
Prevalence_x <<- 1 | ||
Min_Prevalence <<- 1 | ||
Steps_Prevalence <<- 100 | ||
Step_size_Prevalence <<- Max_Prevalence/Steps_Prevalence | ||
Prevalence = seq(Min_Prevalence, (1 + Max_Prevalence), Step_size_Prevalence) #With (1 + Max_Prevalence) we get 101. If we use Max_Prevalence we get 100 | ||
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# PPV Calculation ------------------------------------------------------------- | ||
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# We calculate the 100x100 PPV matrix using %o% (outer) | ||
PPV <<- (Sensitivity * Prevalence_x) / ((Sensitivity * Prevalence_x) + ((Prevalence - 1) %o% FP) ) | ||
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#Label columns and rows of matrix | ||
colnames(PPV) = FP | ||
rownames(PPV) = Prevalence | ||
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# Long format para ggplot Heatmap | ||
PPV_melted = melt(PPV) | ||
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# Give names to variables | ||
names(PPV_melted) = c("melted_Prevalence", "melted_FP", "melted_PPV") | ||
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PPV_melted <<- PPV_melted | ||
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# NPV Calculation ------------------------------------------------------------- | ||
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# As NPV is more dependent on Sensitivity, the x axis should show Sensitivity, and FP should be fixed | ||
NPV <<- ((Prevalence - 1) %o% (100 - FP)) / (((Prevalence - 1) %o% (100 - FP)) + (Prevalence_x * (100 - Sensitivity))) | ||
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#Label columns and rows of matrix | ||
colnames(NPV) = FP | ||
rownames(NPV) = Prevalence | ||
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# Long format para ggplot Heatmap | ||
NPV_melted = melt(NPV) | ||
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# Give names to variables | ||
names(NPV_melted) = c("melted_Prevalence", "melted_FP", "melted_NPV") | ||
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NPV_melted <<- NPV_melted | ||
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# HACK to easily switch betweeen NPV and PPV | ||
if (PPV_NPV == "NPV") { | ||
PPV_melted = NPV_melted | ||
} | ||
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} |
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