CNV.fit: CNV.fit

In conumee: Enhanced copy-number variation analysis using Illumina DNA methylation arrays

Description

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

Usage

CNV.fit(query, ref, anno, ...)

## S4 method for signature 'CNV.data,CNV.data,CNV.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.

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.

Value

CNV.analysis object.

Author(s)

Volker Hovestadt [e-mail]

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'

conumee documentation built on Nov. 8, 2020, 6 p.m.