pumaDE {puma} | R Documentation |
The function generates lists of genes ranked by probability of differential expression (DE). This uses the PPLR method.
pumaDE( eset , design.matrix = createDesignMatrix(eset) , contrast.matrix = createContrastMatrix(eset) )
eset |
An object of class ExpressionSet . |
design.matrix |
A design matrix |
contrast.matrix |
A contrast matrix |
A separate list of genes will be created for each contrast of interest.
Note that this class returns a DEResult-class
object. This object contains information on both the PPLR statistic values (which should generally be used to rank genes for differential expression), as well as fold change values (which are generally not recommended for ranking genes, but which might be useful, for example, to use as a filter). To understand more about the object returned see DEResult-class
, noting that when created a DEResult object with the pumaDE function, the statistic
method should be used to return PPLR values. Also note that the pLikeValues
method can be used on the returned object to create values which can more readily be compared with p-values returned by other methods such as variants of t-tests (limma, etc.).
While it is possible to run this function on data from individual arrays, it is generally recommended that this function is run on the output of the function pumaComb
(which combines information from replicates).
An object of class DEResult-class
.
Richard D. Pearson
Related methods calculateLimma
, calculateFC
, calculateTtest
, pumaComb
, mmgmos
, pplr
, createDesignMatrix
and createContrastMatrix
data(affybatch.example) varLabels(affybatch.example) <- c("level") pData(affybatch.example) <- data.frame("level"=c("twenty","twenty","ten") , "batch"=c("A","B","A"), row.names=rownames(pData(affybatch.example))) eset_mmgmos <- mmgmos(affybatch.example) eset_comb <- pumaComb(eset_mmgmos) pumaDEResults <- pumaDE(eset_comb) topGeneIDs(pumaDEResults,6) # Gives probeset identifiers topGenes(pumaDEResults,6) # Gives row numbers statistic(pumaDEResults)[topGenes(pumaDEResults,6),] # PPLR scores of top six genes FC(pumaDEResults)[topGenes(pumaDEResults,6),] # Fold-change of top six genes