regularizeRaw: Function to perform Baldi & Long's error regularization

In jweile/tileseqMave: TileSeq MAVE Analysis pipeline

Function to perform Baldi & Long's error regularization

Description

Function to perform Baldi & Long's error regularization

Usage

regularizeRaw(
  msc,
  condNames,
  tiles,
  n,
  pseudo.n,
  modelFunctions,
  pessimistic = TRUE
)

Arguments

msc	dataframe containing the output of the 'mean.sd.count()' function
condNames	the names of the different count conditions (select, nonselect etc)
n	the number of replicates present for each datapoint in each condition
pseudo.n	the number of pseudo-replicates that detemine the weight of the prior in the regularization

Value

a data.frame containing for each condition the possion prior, bayesian regularized, and pessimistic (maximum) standard deviation.

jweile/tileseqMave documentation built on April 5, 2024, 4:51 p.m.