normalizeArrayData: Normalize tiling array data

In benja0x40/MRA.TA: Multi Resolution Analysis of Tiling Arrays

Normalize tiling array data

Description

Normalize tiling array data

Usage

normalizeArrayData(
  A,
  M,
  smoothness = 0.08,
  epsilon = 0.01,
  nsteps = 11,
  name = "Test",
  plots = TRUE,
  lowess = T,
  lowess.f = 0.2,
  lowess.mad = 0,
  lowess.iter = 5
)

Arguments

A
M
smoothness
epsilon
nsteps
name
plots
lowess
lowess.f
lowess.mad
lowess.iter

Author(s)

Benjamin Leblanc

See Also

backgroundBiasEstimation, backgroundBiasCorrection, lowessCorrection

Examples

# Load array data and apply background bias estimation+correction, followed by
# lowess normalization

data(WT.4C.Fab7.dm6)

# 1. Combined procedure ------------------------------------------------------

# Raw A and M values
A <- (log2(r1.4C$PM) + log2(r1.ct$PM))/2
M <- (log2(r1.4C$PM) - log2(r1.ct$PM))

# Normalized A and M values
res <- normalizeArrayData(
  A, M, name="4C_norm", plots=TRUE
)
A <- res$A; M <- res$M

# 2. Equivalent step by step procedure ---------------------------------------

# Raw A and M values
A <- (log2(r1.4C$PM) + log2(r1.ct$PM))/2
M <- (log2(r1.4C$PM) - log2(r1.ct$PM))

# Estimate background bias
bb.r1 <- backgroundBiasEstimation(A, M, plots = T)

# Correct background bias
res <- backgroundBiasCorrection(A, M, theta=bb.r1)
A <- res$x; M <- res$y

# Apply lowess normalization
res <- lowessCorrection(A, M, lowess.f=0.2, plots = T)
A <- res$x; M <- res$y

benja0x40/MRA.TA documentation built on March 13, 2023, 5:15 a.m.