maigesPack (version 1.36.0)

maiges-class: maiges class, store normalised microarray datasets

Description

This class describes objects to handle ratio of intensities (W) and average of intensities (A) values values and information about genes and samples used in the data. Objects of this class are created from class maigesRaw using the functions normLoc, normOLIN, normRepLoess, normScaleLimma and/or normScaleMarray to do the normalisation.

Here, the M=log(R/G) value of intensity ratio was redefined as W=log(Test/Ref), where Test and Ref are the test and reference samples.

Slots

W:

numeric matrix containing the ratio values (in log2 scale) between the test and reference sample intensities (W values). Spots are indexed by rows and samples by columns.

A:

numeric matrix containing the mean intensity values between test and reference samples (also in log2 scale). Spots corresponding to rows and samples (or chips) corresponding to columns, too.

SD:

numeric matrix containing the standard deviation of W values when the lowess step is repeated several times.

IC1:

numeric matrix containing the left margin of confidence interval defined by repeated lowess during the normalisation step.

IC2:

numeric matrix containing the right margin of confidence interval defined above.

BadSpots:

logical vector specifying spots that was judged as bad ones. By default this slot is created as a vector of FALSEs with same length as number of spots.

UseSpots:

logical matrix indexing the spots to be used for normalisation.

GeneGrps:

a logical matrix with rows representing the spots and columns representing different gene groups. Each column give the index of spots in that gene group.

Paths:

list containing 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:

a list containing the number of rows (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:

data frame giving the gene labels. These labels are generally used during the data analysis.

Slabels:

data frame giving the sample labels. These labels are generally used during the data analysis.

Notes:

char string that receives any comment about the dataset. The dataset description is stored in this slot.

Date:

char string giving the date and hour that the object was created.

V.info:

list containg three characters. The first one is a string containing the R version used when the object was created. The second is a char vector with base packages and the last one is another char vector with additional packages and version numbers.

Methods

[

signature(x = 'maiges'): subsetting operator for spots on the array or arrays in the batch, ensures that all slots are subset properly.

boxplot

signature(x = 'maiges'): boxplot method for maiges class. Display boxplots of the slides and print tip groups using package marray or boxplots of one gene previously defined.

dim

signature(x = 'maiges', value = 'numeric'): get the dimensions of the object, numeric vector of length two.

image

signature(x = 'maiges'): image method for maiges class. Display colour representation of the slides using package marray.

plot

signature(x = 'maiges'): plot method for maiges class. Display 'MA' plots.

print

signature(x = 'maiges'): print method for maiges class.

show

signature(x = 'maiges'): show method for maiges class.

summary

signature(x = 'maiges'): summary method for maiges class.

Details

This defines the main class of objects defined in this package. It is created from maigesRaw class using the normalisation functions normLoc, normOLIN, normRepLoess, normScaleLimma and normScaleMarray. From this class of objects it is possible to do any type of analysis defined by several functions in this package. Also, it is possible to summarise spots (or samples) information using the function summarizeReplicates.

See Also

normLoc, normOLIN, normRepLoess, normScaleLimma, normScaleMarray and summarizeReplicates.