# Utility functions for the EBarrays package

### Description

Utilitiy functions for the EBarrays package

### Usage

1 |

### Arguments

`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 |

`ordered` |
logical variable specifying whether the pattern is ordered or not |

### Details

`ebPatterns`

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

.

### Value

`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.

### Author(s)

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

### References

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.

### See Also

`emfit`

### Examples

1 2 3 4 |

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