plot_pr: Plot a precision-recall curve for a list of protein-protein...

In fosterlab/CFTK: The Co-Fractionation Toolkit

Description

Assess the intrinsic quality of a CF-MS dataset by evaluating the precision of the interaction network for any number of interactions scored. The x-axis in the output plot represents the total number of interactions (and can optionally be subset to a limited range), while the y-axis shows the precision for each point in the ranked list.

Usage

plot_pr(pairs, max_n = NULL)

Arguments

pairs

a data frame in which each row represents a protein pair, and which contains the following columns: score: the score assigned to that protein pair, e.g., by a machine-learning classifier, in which higher scores represent a greater probability of a physical interaction label: a ground-truth annotation of whether that pair of proteins is known to physically interact; one of 1, 0, or NA (not labelled)

max_n

optionally, plot the precision-recall curve only out to this maximum number of interactions

Details

Note that the x-axis shows recall in terms of the total number of interactions in the CF-MS dataset, not the proportion of true-positive interactions recovered from the 'gold standard' dataset, since many of these interactions may not have been detected by CF-MS.

Value

a ggplot2 object plotting the precision-recall curve for the input interactions

fosterlab/CFTK documentation built on Jan. 19, 2021, 10:31 p.m.