Description Usage Arguments Value See Also Examples

View source: R/fn_significance.R

This method uses pre-computed covariance matrices that were created for various gene-gene correlations (0.2 to 0.9 in steps of 0.1) and number of miRNAs (between 1 and 8) under the null hypothesis that the sensitivity correlation is zero. Datasets are sampled from this null model and allow for an empirical p-value to be computed that is only significant if the sensitivity correlation is higher than can be expected by chance given the number of samples, correlation and number of miRNAs. p-values are adjusted indepdenently for each parameter combination using Benjamini-Hochberg FDR correction.

1 | ```
sponge_compute_p_values(sponge_result, null_model, log.level = "ERROR")
``` |

`sponge_result` |
A data frame from a sponge call |

`null_model` |
optional, pre-computed simulated data |

`log.level` |
The log level of the logging package |

A data frame with sponge results, now including p-values and adjusted p-value

sponge_build_null_model

1 2 | ```
sponge_compute_p_values(ceRNA_interactions,
null_model = precomputed_null_model)
``` |

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