GetPatterns: Generate all possible patterns in a multiple condition study

Description Usage Arguments Value Author(s) References Examples

View source: R/GetPatterns.R

Description

'GetPatterns' generates all possible patterns in a multiple condition study.

Usage

1
GetPatterns(Conditions)

Arguments

Conditions

The names of the Conditions in the study.

Value

A matrix describe all possible patterns.

Author(s)

Ning Leng

References

Ning Leng, John A. Dawson, James A. Thomson, Victor Ruotti, Anna I. Rissman, Bart M.G. Smits, Jill D. Haag, Michael N. Gould, Ron M. Stewart, and Christina Kendziorski. EBSeq: An empirical Bayes hierarchical model for inference in RNA-seq experiments. Bioinformatics (2013)

Examples

1
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Conditions = c("C1","C1","C2","C2","C3","C3")
PosParti = GetPatterns(Conditions)

Example output

Loading required package: blockmodeling
To cite package 'blockmodeling' in publications please use package
citation and (at least) one of the articles:

  <U+017D>iberna, Ale<U+0161> (2007). Generalized blockmodeling of valued networks.
  Social Networks 29(1), 105-126.

  <U+017D>iberna, Ale<U+0161> (2008). Direct and indirect approaches to blockmodeling
  of valued networks in terms of regular equivalence. Journal of
  Mathematical Sociology 32(1), 57<U+2013>84.

  ?iberna, Ale? (2018).  Generalized and Classical Blockmodeling of
  Valued Networks, R package version 0.3.4.

To see these entries in BibTeX format, use 'print(<citation>,
bibtex=TRUE)', 'toBibtex(.)', or set
'options(citation.bibtex.max=999)'.
Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess

Loading required package: testthat

EBSeq documentation built on Nov. 8, 2020, 6:52 p.m.