Description Usage Arguments Details Value Author(s) References Examples

To transform count data into Gaussian distributed and also keep the consistency for contructing networks.

1 | ```
Cont2Gaus(iData,total_iteration=5000,stepsize=0.05)
``` |

` iData ` |
a |

` total_iteration ` |
Total iteration number for Baysian random effect model-based transformation, default of 5000. |

` stepsize ` |
The stepsize of updating parameters in transformation, default of 0.05. |

This is the function that transform the count data into Gaussian data which include two steps. First, we do data continuized transformation `ContTran(data,...)`

and then we apply the semiparametric transformation (Liu, H et al, 2009) provided in huge packages to tranform continuized data into Gaussian distributed.

`Gaus` |
A |

Bochao Jiajbc409@gmail.com and Faming Liang

Jia, B., Xu, S., Xiao, G., Lamba, V., Liang, F. (2017) Inference of Genetic Networks from Next Generation Sequencing Data. Biometrics.

Liu, H., Lafferty, J. and Wasserman, L. (2009). The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. Journal of Machine Learning Research , 10, 2295-2328.

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