'LogNMulti' specifies the function to run (one round of) the EM algorithm for the NB-beta model in the multiple condition test.

1 2 3 | ```
LogNMulti(Input, InputSP, EmpiricalR, EmpiricalRSP,
NumOfEachGroup, AlphaIn, BetaIn, PIn,
NoneZeroLength, AllParti, Conditions)
``` |

`Input, InputSP` |
The expressions among all the samples. |

`NumOfEachGroup` |
Number of genes in each Ng group. |

`AlphaIn, PIn, BetaIn, EmpiricalR, EmpiricalRSP` |
The parameters from the last EM step. |

`NoneZeroLength` |
Number of Ng groups. |

`AllParti` |
The patterns of interests. |

`Conditions` |
The condition assignment for each sample. |

Ning Leng

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)

1 2 3 4 5 6 7 8 9 | ```
#
#Input = matrix(rnorm(100,100,1),ncol=10)
#rownames(Input) = paste("g",1:10)
#RIn = matrix(rnorm(100,200,1), ncol=10)
#res = LogNMulti(Input, list(Input[,1:5], Input[,6:10]),
# RIn, list(RIn[,1:5], RIn[,6:10]), 10, .6, .7,
# c(.3,.7), 1, rbind(c(1,1), c(1,2)),
# as.factor(rep(c("C1","C2"), each=5)))
``` |

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