opa {oppar} | R Documentation |
Returns a matrix with 0, -1 and 1 entries that describe outlier profiles in samples. The rows reperesent genes and the columns represent samples. -1 implies that the gene is a down-regulated outlier, 1 indicates an up-regulate outlier and 0 means that the gene is not an outlier in a sample.
opa(exprs.matrix, ...) ## S4 method for signature 'matrix' opa(exprs.matrix, group, upper.quantile = 0.95, lower.quantile = 0.05) ## S4 method for signature 'ExpressionSet' opa(exprs.matrix, group, upper.quantile = 0.95, lower.quantile = 0.05)
exprs.matrix |
Gene expression data. Can be either a matrix or an object of type ExpressionSet. |
... |
Numeric. To supply values for upper.quantile and lower.quantile arguments if default values are going to be override. |
group |
A vector of factors representing the groups to which each sample belong. This can be either a vector of 0s and 1s, or normal and cases. |
upper.quantile |
Numeric. The cut-off for upper quantile when determining outliers. Default to 0.95 |
lower.quantile |
Numeric. The cut-off for lower quantile when determining outliers. Default to 0.05 |
opa
returns an object of type OPPARList
. The outlier profiles
are stored in profileMatrix
and can be accessed using $. It it also
possible to retrieve parameters used to run the outlier profile analysis, such
as upper.quantile
, lower.quantile
via the $ operator.
matrix
: opa(exprs.matrix, group, lower.quantile = 0.05, upper.quantile = 0.95)
ExpressionSet
: opa(eset, group, lower.quantile = 0.05, upper.quantile = 0.95)
Wang, C., Taciroglu, A., Maetschke, S. R., Nelson, C. C., Ragan, M. A., & Davis, M. J. (2012). mCOPA: analysis of heterogeneous features in cancer expression data. Journal of Clinical Bioinformatics, 2, 22. http://doi.org/10.1186/2043-9113-2-22
# loading bcm object from GSE46141 dataset data(GSE46141) library(Biobase) # defining the group variable. local breast tumors are the controls # and the rest of the samples are the diseased samples group <- sapply(pData(bcm)$source_name_ch1, function(x){ ifelse(x == "breast",0,1)}) group <- factor(group) # running opa with default values (i.e upper.quantile = 0.95, lower.quantile = 0.05) # the result is an object of type OPPARList opa(bcm,group = group)