FAMT (version 2.6)

defacto: FAMT factors description

Description

This function helps the user to describe and interpret the factors using some available external information on either genes or arrays. Diagnostic plots are provided.

Usage

defacto(model, plot = TRUE, axes = c(1, 2), select.covar = NULL, 
select.annot = NULL, lim.b = 0.01, lab = TRUE, cex = 1)

Arguments

model

'FAMTmodel' object

plot

Boolean (TRUE by default). If TRUE, diagnostic plots are provided (unless the 'FAMTmodel' has less than one factor).

axes

Vector of length 2, specifying the factors to plot.

select.covar

Selection of external covariates. If NULL (default value), the function takes all covariates except the array identifiers and those used in the model.

select.annot

Selection of external annotations. If NULL (default value), the function takes all the available factors in 'annotations'.

lim.b

Proportion of variables with the highest loadings for each factor to appear on plots or in tables (0.01 by default).

lab

Boolean. If TRUE (default value), array names are labeled on the figure

cex

A numerical value giving the amount by which plotting text and symbol should be enlarged relative to the default (1 is the default value)

Value

loadings

highest loadings (B matrix) for each factor. The proportion of loading is determined by "lim.b"

covariates

Matrix of p-values for the tests of linear relationships between scores on each factor (rows) and external covariates (columns).

annotations

Matrix of p-values for the tests of linear relationships between loadings of each factor (rows) and external annotations (columns).

See Also

as.FAMTdata, modelFAMT

Examples

# NOT RUN {
## FAMT data
data(expression)
data(covariates)
data(annotations)

# Create the 'FAMTdata'
############################################
chicken = as.FAMTdata(expression,covariates,annotations,idcovar=2)
# 'FAMTdata' summary 
# }
# NOT RUN {
summaryFAMT(chicken)
# }
# NOT RUN {
# FAMT complete multiple testing procedure
############################################
model = modelFAMT(chicken,x=c(3,6),test=6,nbf=3)
# summary on the 'FAMT model'
# }
# NOT RUN {
summaryFAMT(model)
# }
# NOT RUN {
# Factors description
############################################
chicken.defacto = defacto(model,axes=1:2,select.covar=4:5,select.annot=3:6,
cex=0.6)
# }