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edge (version 2.4.2)

build_study: Formulates the experimental models

Description

build_study generates the full and null models for users unfamiliar with building models in R. There are two types of experimental designs: static and time-course. For more details, refer to the vignette.

Usage

build_study(data, grp = NULL, adj.var = NULL, bio.var = NULL,
  tme = NULL, ind = NULL, sampling = c("static", "timecourse"),
  basis.df = 2, basis.type = c("ncs", "poly"))

Arguments

data
matrix: gene expression data (rows are genes, columns are samples).
grp
vector: group assignement in the study (for K-class studies). Optional.
adj.var
matrix: adjustment variables. Optional.
bio.var
matrix: biological variables. Optional.
tme
vector: time variable in a time course study. Optional.
ind
factor: individual factor for repeated observations of the same individuals. Optional.
sampling
string: type of study. Either "static" or "timecourse". Default is "static".
basis.df
numeric: degrees of freedom of the basis for time course study. Default is 2.
basis.type
string: either "ncs" (natural cubic spline) or "ps" (polynomial spline) basis for time course study. Default is "ncs".

Value

  • deSet object

See Also

deSet, build_models

Examples

Run this code
# create ExpressionSet object from kidney dataset
library(splines)
data(kidney)
age <- kidney$age
sex <- kidney$sex
kidexpr <- kidney$kidexpr

# create deSet object from data
de_obj <- build_study(data = kidexpr, adj.var = sex, tme = age,
sampling = "timecourse", basis.df = 4)

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