estimateAbundance: Estimate log2-abundances of PTM sites or proteins

In MSstatsPTM: Statistical Characterization of Post-translational Modifications

Description

estimateAbundance takes as input the summarized log2-intensities for each PTM site, performs statistical modeling for the abundance of the site, and returns the estimates of model parameters for all sites in all experimental conditions.

Usage

estimateAbundance(df, fctBatch = FALSE, perProtein = FALSE)

Arguments

df	A data frame with columns of protein, site, group, run, log2inty, and possibly, batch.
fctBatch	A logical. TRUE considers a fixed batch effect, FALSE otherwise. Default is FALSE.
perProtein	A logical. TRUE ignores the site-level information for PTM and considers protein as a whole, FALSE otherwise. Default is FALSE.

Value

A list of two elements named PTM and PROTEIN. The PTM list has four elements: protein (a string vector of protein names), site (a string vector of PTM sites), param (a list of model parameter estimates for each site), and df (a numeric vector of degrees of freedom for each model). The PROTEIN list includes all as in PTM, except site.

Examples

sim <- PTMsimulateExperiment(
    nGroup=2, nRep=2, nProtein=1, nSite=1, nFeature=5,
    logAbundance=list(
        PTM=list(mu=25, delta=c(0, 1), sRep=0.2, sPeak=0.05),
        PROTEIN=list(mu=25, delta=c(0, 1), sRep=0.2, sPeak=0.05)
    )
)
s <- PTMsummarize(sim)
estimateAbundance(s[["PTM"]])
estimateAbundance(s[["PROTEIN"]], perProtein=TRUE)

MSstatsPTM documentation built on Nov. 8, 2020, 5:49 p.m.