maigesRaw-class {maigesPack} | R Documentation |
This class describes objects to handle intensity values and information
about genes and samples used in the data. Objects of this class are
obtained from class maigesPreRaw
using function
createMaigesRaw
.
This class of objects defines a real raw object that is used to do the
normalisation. Objects of this class are generated from objects of
class maigesPreRaw
using the function
createMaigesRaw
. Here it is possible to do several
plots for exploratory analysis using functions from
marray package. Using the function
selSpots
, you select spots to use in the normalisation
method, that is done by the functions normLoc
, normOLIN
,
normRepLoess
, normScaleLimma
and
normScaleMarray
.
Sf
:Sb
:Sdye
:Rf
:Rf
:Rdye
:Flag
:BadSpots
:UseSpots
:GeneGrps
:Paths
:graphNEL
objects
specifying gene regulatory networks (or pathways). The first
object in this list is a char string giving the gene label used to
match the genes.Layout
:gridR
) and
columns (gridC
) of grids, the number of rows (spotR
)
and columns (spotC
) of spots inside each grid and the total
number of spots.Glabels
:Slabels
:Notes
:Date
:V.info
:signature(x = 'maigesRaw')
: subsetting operator for
spots on the array or arrays in the batch, ensures that all slots
are subset properly.signature(x = 'maigesRaw')
: boxplot method for
maigesRaw
class. Display boxplots of the slides and
print tip groups using package marray.signature(x = 'maigesRaw', value = 'numeric')
: get
the dimensions of the object, numeric vector of length two.signature(x = 'maigesRaw')
: image method for
maigesRaw
class. Display colour representation of
the slides using package marray.signature(x = 'maigesRaw')
: plot method for
maigesRaw
class. Display MA plots.signature(x = 'maigesRaw')
: print method for
maigesRaw
class.signature(x = 'maigesRaw')
: show method for
maigesRaw
class.signature(x = 'maigesRaw')
: summary method for
maigesRaw
class.Gustavo H. Esteves <gesteves@vision.ime.usp.br>
createMaigesRaw
, selSpots
,
normLoc
, normOLIN
,
normRepLoess
, normScaleLimma
and
normScaleMarray
.