normalizeGcContent: Normalizes signals for GC-content effects

In HenrikBengtsson/aroma.seq: High-Throughput Sequence Analysis using the Aroma Framework

Description

Normalizes signals for GC-content effects. Some or all signals are used to estimated the normalization function. All signals are normalized.

Usage

## Default S3 method:
normalizeGcContent(y, gcContent, targetFcn=NULL, subsetToFit=NULL,
  onMissing=c("ignore", "median"), .isLogged=TRUE, ..., .returnFit=FALSE)

Arguments

y	A numeric vector of length K of signals to be normalized.
gcContent	A numeric vector of GC fractions.
targetFcn	An optional function. If NULL, the data is normalized to have constant GC content effects (all equal to zero on the log-scale).
subsetToFit	The subset of data points used to fit the normalization function. If NULL, all data points are considered.
onMissing	Specifies how data points for which there is no fragment length is normalized. If "ignore", the values are not modified. If "median", the values are updated to have the same robust average as the other data points.
.isLogged	A logical.
...	Additional arguments passed to lowess.
.returnFit	A logical.

Value

Returns a numeric vector of the normalized signals.

Author(s)

Henrik Bengtsson

HenrikBengtsson/aroma.seq documentation built on Feb. 15, 2021, 2:21 a.m.