conumee (version 1.4.2)

CNV.fit: CNV.fit

Description

Normalize query sample intensities by fitting intensities to reference set using a linear regression model.

Usage

CNV.fit(query, ref, anno, ...)
"CNV.fit"(query, ref, anno, name = NULL, intercept = TRUE)

Arguments

query

CNV.data object of query sample (single sample).

ref

CNV.data object of reference set.

anno

CNV.anno object. Use CNV.create_anno do create.

...

Additional parameters (CNV.fit generic, currently not used).

name

character. Optional parameter to set query sample name.

intercept

logical. Should intercept be considered? Defaults to TRUE.

Value

CNV.analysis object.

Details

The log2 ratio of query intensities versus a linear combination of reference set intensities that best reflects query intensities is calculated (as determined by linear regression). The annotations provided to CNV.fit are saved within the returned CNV.analysis object and used for subsequent analysis steps.

Examples

# prepare
library(minfiData)
data(MsetEx)
d <- CNV.load(MsetEx)
data(detail_regions)
anno <- CNV.create_anno(detail_regions = detail_regions)

# create object
x <- CNV.fit(query = d['GroupB_1'], ref = d[c('GroupA_1', 'GroupA_2', 'GroupA_3')], anno)

# modify object
#x <- CNV.bin(x)
#x <- CNV.detail(x)
#x <- CNV.segment(x)

# general information
x
show(x)

# coefficients of linear regression
coef(x)

# show or replace sample name
names(x)
names(x) <- 'Sample 1'