swinsor_vector: Smooth Winsor Normalization

In sidiropoulos/RNAprobR-old: An R package for analysis of massive parallel sequencing based RNA structure probing data

Description

Function performs Winsor normalization (see winsor() function) of each window of specified window_size, sliding in a given vector by 1 position, and reports a list of (1) mean Winsorized values for each vector position (mean of Winsorized value for a given position as calculated within each overlapping window) and (2) standard deviation of those Winsorized values.

Usage

swinsor_vector(input_vector, window_size, winsor_level = 0.9,
  only_top = FALSE)

Arguments

input_vector	Vector with values to be smooth-Winsorized
window_size	Size of a sliding window.
winsor_level	Winsorization level. Bottom outliers will be set to (1-winsor_level)/2 quantile and top outliers to (1+winsor_level)/2 quantile.
only_top	If TRUE then bottom values are not Winsorized and are set to 0.

Value

comp1	Vector with mean Winsorized values for each input_vector position
comp2	Vector with standard deviation of Winsorized values for each input_vector position

Author(s)

Lukasz Jan Kielpinski

References

"Analysis of sequencing based RNA structure probing data" Kielpinski, Sidiropoulos, Vinther. Chapter in "Methods in Enzymology" (in preparation)

Examples

data_set <- runif(1:100)*100
plot(swinsor_vector(data_set, window_size=71,
                    winsor_level=0.8)[[1]] ~ data_set)

sidiropoulos/RNAprobR-old documentation built on May 29, 2019, 9:58 p.m.