Description Usage Arguments See Also Examples

This function fits a zero-truncated negative binomial distribution to the positive counts for each feature (row). By default, the zero-truncated negative binomial distribution from the `gamlss`

package is used for this function.

1 2 | ```
getDatasetZTNB(counts, design, drop.extreme.dispersion = FALSE,
offset = NULL)
``` |

`counts` |
A numeric matrix containing gene expression counts. Note that every gene in this matrix must have at least $p+1$ positive counts, with $p$ the number of columns in the design matrix. |

`design` |
The design of the experiments with rows corresponding to samples and columns corresponding to coefficients. |

`drop.extreme.dispersion` |
Either a numeric value between $0$ and $1$, stating the proportion of genes with extreme (high) dispersions to remove for simulation, or FALSE (default), if no dispersions should be removed for the analysis. |

`offset` |
The offset to use (typically the sequencing depth) when estimating gene-wise means and dispersions in the zero-truncated negative binomial model. These parameters will be used as a basis for the simulation. |

1 2 3 4 | ```
data(islamEset,package="zingeR")
islam=exprs(islamEset)[1:2000,]
design=model.matrix(~pData(islamEset)[,1])
params = getDatasetZTNB(counts=islam, design=design)
``` |

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