R: Estimate 4sU dropout percentages

dropoutpercent {grandR}

R Documentation

Estimate 4sU dropout percentages

Description

For several potential reasons, a sample specific percentage of reads from labelled RNA might be lost. This percentage can be estimated from data of this sample and an equivalent 4sU naive control (see details).

Usage

Estimate4sUDropoutPercentage(data, pairs = Findno4sUPairs(data), ...)

Estimate4sUDropoutPercentageForSample(
  data,
  w4sU,
  no4sU,
  ntr = w4sU,
  LFC.fun = lfc::PsiLFC,
  type = c("spearman", "quantreg", "linear", "lowess"),
  bootstrap = FALSE
)

Arguments

`data`	a grandR object
`pairs`	a no4sU pairs list as generated by Findno4sUPairs
`...`	further arguments to be passed to or from other methods.
`w4sU`	the name of a 4sU sample
`no4sU`	the name(s) of equivalent no4sU sample(s)
`ntr`	the name of a sample to take NTRs from (usually equal to w4sU)
`LFC.fun`	function to compute log fold change (default: PsiLFC, other viable option: NormLFC)
`type`	one of "spearman","quantreg","linear" or "lowess" (see details)
`bootstrap`	if TRUE, perform a single bootstrap sample (by drawing genes with replacement)

Details

The percentage of 4sU dropout is estimated by numerical optimization of the factor f that has to be multiplied with the NTR to mitigate the effect of 4sU dropout. The exact objective function depends on the type parameter:

spearman: f is estimated such that the spearman correlation coefficient of the log2 fold change 4sU/no4sU vs the ntr rank is 0
quantreg: f is estimated such that the slope of a median regression with the the ntr rank as independent variable and the log2 fold change 4sU/no4sU as dependent variable is 0
linear: f is estimated such that the slope of a linear regression with the the ntr rank as independent variable and the log2 fold change 4sU/no4sU as dependent variable is 0
lowess: f is estimated by minimizing the sum-of-squares of the residuals from a lowess regression with the the ntr rank as independent variable and the log2 fold change 4sU/no4sU as dependent variable is 0

Once f is computed the percentage of 4sU dropout is f/(f+1).

Value