Description Usage Arguments Value Examples

View source: R/core_functions.R

'NMF_RNA_Tang_ind' is a upper level wrapper function for 'NMF_RNA_Tang'. On top of core NMF, it also initialtes $W$ and $H$, and scales/normalizes according to the input arguments: scale_Data and reg_para. Besides, it also does random permutations to check results stability and helps choose the best parameters. Although it has full sets of NITUMID's functions, the 'NMF_RNA_Tang_ind' is still not supposed to be run independently, has hyper-function will call it with different parameters choices.

1 2 3 | ```
NMF_RNA_Tang_ind(Y, lam_W, beta_W, A, eta, tol = 10^-5, prterr = F,
max.itr = 2000, always = F, num_cell = 11, scale_Data,
perm_type = T)
``` |

`Y` |
Y is the gene expression matrix that has #signature genes rows and #samples columns |

`lam_W` |
$\lambda$ is the parameter imposing A's structure into resulting W, see our paper for more info. In real calculation, upper level functions will automatically choose suitable $\lambda$ no need to set by yourself |

`beta_W` |
$\beta$ is the parameter controlling sparsity ridge penalty, see our paper for more information. In real calculation, upper level functions will automatically choose suitable $\beta$ no need to set by yourself |

`A` |
The trichotomous guide matrix A |

`eta` |
$\eta$ is the parameter for ensuring column sums of H are 1s, upper level function will choose suitable $\eta$ automatically, no need to spcify yourself |

`tol` |
numeric scalar, the cutoff value for stop iterating, default $10^-5$ |

`prterr` |
logical value indicating if it should print each step's error, default FALSE |

`max.itr` |
numerical scalar, maximum iteration number, default 2000 |

`num_cell` |
numeric scalar, number of component cell types, dfault 11. Noted that if you were to change component cell types number, you should change your $A$ matrix accordingly. |

`scale_Data` |
the parameter controlling which scaling method to use for $Y$: 0 indicates no scaling, 1 indicates scaling $||Y||_F=\sqrtnm$, where $n,m$ are dimensions of Y; 2 indicates scaling such that $||Y^scaled||_F=||log(Y^raw+1)||_F$ |

`perm_type` |
logical variable, default TRUE. If TRUE, the function will do a permutation and measure consistency between results. |

`ini.W` |
Initial W matrix |

`ini.H` |
Initial H matrx |

`alaways` |
logical, if it should output results whatsover when max.itr is reached, default TRUE |

'NMF_RNA_Tang' returns the resulted W and H, as well as track of errors along iteration

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