meanDifferences: meanDifferences

In mcalgaro93/benchdamic: Benchmark of differential abundance methods on microbiome data

meanDifferences

Description

Compute the differences between the estimated and the observed continuity corrected logarithms of the average count values (MD), and between the estimated average probability to observe a zero and the the observed zero rate (ZPD).

Usage

meanDifferences(estimated, observed)

Arguments

estimated	a two column data.frame, output of fitNB, fitZINB, fitDM, fitZIG, or fitHURDLE functions. More in general, a data frame containing the continuity corrected logarithm for the average of the fitted values for each row of a matrix of counts in the Y column, and the estimated probability to observe a zero in the Y0 column.
observed	a two column data.frame, output of prepareObserved function. More in general, a data frame containing the continuity corrected logarithm for the average of the observed values for each row of a matrix of counts in the Y column, and the estimated proportion of zeroes in the Y0 column.

Value

a data.frame containing the differences between the estimated and the observed continuity corrected logarithms of the average count values in the MD column, and between the estimated average probability to observe a zero and the the observed zero rate in the ZPD column.

See Also

prepareObserved.

Examples

# Randomly generate the observed and estimated data.frames
observed <- data.frame(Y = rpois(10, 5), Y0 = runif(10, 0, 1))
estimated <- data.frame(Y = rpois(10, 5), Y0 = runif(10, 0, 1))

# Compute the mean differences between estimated and observed data.frames
meanDifferences(estimated, observed)

mcalgaro93/benchdamic documentation built on March 10, 2024, 10:40 p.m.