deSet: Create a deSet object from an ExpressionSet

In jdstorey/edge: Extraction of Differential Gene Expression

Description

Creates a deSet object that extends the ExpressionSet object.

Usage

deSet(object, full.model, null.model, individual = NULL)

## S4 method for signature 'ExpressionSet'
deSet(object, full.model, null.model,
  individual = NULL)

Arguments

object	S4 object: ExpressionSet
full.model	formula: full model containing the both the adjustment and the biological variables for the experiment.
null.model	formula: null model containing the adjustment variables for the experiment.
individual	factor: information on repeated samples in experiment.

Value

deSet object

Note

It is essential that the null and full models have the same variables as the ExpressionSet phenoType column names.

Author(s)

John Storey, Andrew Bass

See Also

deSet, odp and lrt

Examples

# import data
library(splines)
data(kidney)
age <- kidney$age
sex <- kidney$sex
kidexpr <- kidney$kidexpr
cov <- data.frame(sex = sex, age = age)
pDat <- as(cov, "AnnotatedDataFrame")
exp_set <- ExpressionSet(assayData = kidexpr, phenoData = pDat)

# create models
null_model <- ~sex
full_model <- ~sex + ns(age, df = 4)

# create deSet object from data
de_obj <- deSet(exp_set, null.model = null_model,
full.model = full_model)

# optionally add individuals to experiment, in this case there are 36
# individuals that were sampled twice
indSamples <- as.factor(rep(1:36, each = 2))
de_obj <- deSet(exp_set, null.model = null_model,
full.model = full_model, ind = indSamples)
summary(de_obj)

jdstorey/edge documentation built on May 18, 2019, 11:35 p.m.