accuracy_sifter {aphylo}

Accuracy calculation as defined in Engelhardt et al. (2011)

Description

Uses SIFTER's 2011 definition of accuracy, where a protein is tagged as accurately predicted if the highest ranked prediction matches it.

Usage

accuracy_sifter(pred, lab, tol = 1e-10, highlight = "", ...)

## S3 method for class 'aphylo_estimates'
accuracy_sifter(pred, lab, tol = 1e-10, highlight = "", ...)

## Default S3 method:
accuracy_sifter(pred, lab, tol = 1e-10, highlight = "", nine_na = TRUE, ...)

Arguments

pred

A matrix of predictions, or an aphylo_estimates object.

lab

A matrix of labels (0,1,NA, or 9 if nine_na = TRUE).

tol

Numeric scalar. Predictions within tol of the max score will be tagged as the prediction made by the model (see deails).

highlight

Pattern passed to sprintf used to highlight predicted functions that match the observed.

...

Further arguments passed to the method. In the case of aphylo_estimates, the arguments are passed to predict.aphylo_estimates().

nine_na

Treat 9 as NA.

Details

The analysis is done at the protein level. For each protein, the function compares the YES annotations of that proteins with the predicted by the model. The algorithm selects the predicted annotations as those that are within tol of the maximum score.

This algorithm doesn't take into account NOT annotations (0s), which are excluded from the analysis.

When highlight = "", no highlight is done.

Value

A data frame with Ntip() rows and four variables. The variables are:

• Gene: Label of the gene

• Predicted: The assigned gene function.

• Observed: The true set of gene functions.

• Accuracy: The measurement of accuracy according to Engelhardt et al. (2011).

Examples

set.seed(81231)
atree <- raphylo(50, psi = c(0,0), P = 3)
ans <- aphylo_mcmc(atree ~ mu_d + mu_s + Pi)

accuracy_sifter(ans)