utilities: Utility functions for the EBarrays package
In EBarrays: Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification

Description Usage Arguments Details Value Author(s) References See Also Examples

Utilitiy functions for the EBarrays package

1	ebPatterns(x, ordered=FALSE)

`x`	x can be a character vector (of length > 2) (see example), or an arbitrary connection which should provide patterns, one line for each pattern. If `x` is a character vector of length 1, it is assumed to be the name of a file (since there's no point in a patterns object with only one pattern) which is then opened and treated as a connection.
`ordered`	logical variable specifying whether the pattern is ordered or not

ebPatterns creates objects that represent a collection of hypotheses to be used by emfit.

ebPatterns creates an Object of class “ebarraysPatterns”, to be used in other functions such as emfit. This is nothing more than a list (and can be treated as such as far as indexing goes) and is used only for method dispatch.

Ming Yuan, Ping Wang, Deepayan Sarkar, Michael Newton, and Christina Kendziorski

Newton, M.A., Kendziorski, C.M., Richmond, C.S., Blattner, F.R. (2001). On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarray data. Journal of Computational Biology 8:37-52.

Kendziorski, C.M., Newton, M.A., Lan, H., Gould, M.N. (2003). On parametric empirical Bayes methods for comparing multiple groups using replicated gene expression profiles. Statistics in Medicine 22:3899-3914.

Newton, M.A. and Kendziorski, C.M. Parametric Empirical Bayes Methods for Microarrays in The analysis of gene expression data: methods and software. Eds. G. Parmigiani, E.S. Garrett, R. Irizarry and S.L. Zeger, New York: Springer Verlag, 2003.

Newton, M.A., Noueiry, A., Sarkar, D., and Ahlquist, P. (2004). Detecting differential gene expression with a semiparametric hierarchical mixture model. Biostatistics 5: 155-176.

Yuan, M. and Kendziorski, C. (2006). A unified approach for simultaneous gene clustering and differential expression identification. Biometrics 62(4): 1089-1098.

emfit

patterns <- ebPatterns(c("1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1",
                         "1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2
                          2 2 2"), TRUE)
show(patterns)