Description Objects from the Class Slots Methods References Examples
This is a class representation for the effect size estimates and other summary information from a single gene expression study, usually constructed in preparation for meta-analysis.
Objects can be created using the functions getPLM.es
or new
.
gn
:Object of class character
representing the probeset IDs of the genes in the study.
ES.mat
:Object of class matrix
representing the effect size estimates for each gene in the study.
Rows correspond to probesets and columns correspond to different comparisons or tests of differential expression.
If a test of differential expression was performed for different covariate levels, then there will be more than
one column, so that each row in this matrix represents a vector of effect size estimates for the corresponding probeset
in the gn
slot.
Cov.mat
:Object of class matrix
, with each row representing the upper triangle of the variance / covariance
matrix of the vector of effect size estimates (row in the ES.mat
slot) for the corresponding probeset in the gn
slot.
Within each row, the order is the same as the result of a call to the upperTriangle(matrix,diag=T)
function in the gdata package.
chip
:Object of class character
representing the chip or array version used in the study.
covariates
:Object of class data.frame
representing covariate differences among the columns of the matrix in the ES.mat
slot.
This object has a row for each column of the matrix in the ES.mat
slot, and a column for each covariate to be considered in the
meta-analysis, regardless of whether the covariate takes on multiple values in the study represented in this ES.obj
object.
For best interpretability, columns of the data.frame
in this covariates
slot should be coded as 0/1.
dep.grp
Object of class integer
representing the dependence group number assigned to the study.
Studies from the same research team may be considered hierarchically dependendent and share the same dep.grp
value.
replace the slot entries
Stevens J.R. and Nicholas G. (2009), metahdep: Meta-analysis of hierarchically dependent gene expression studies, Bioinformatics, 25(19):2619-2620.
See also the metahdep package vignette.
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### See the metahdep package vignette for a full example
###
data(HGU.DifExp.list)
ES <- HGU.DifExp.list[[1]]
slotNames(ES)
head(ES@gn)
head(ES@ES.mat)
head(ES@Cov.mat)
ES@chip
ES@covariates
ES@dep.grp
|
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