Description Usage Arguments Value Author(s) Examples

This function takes the results from function `generateNull()`

and plots the density curves of permuted scores for the provided samples via
`sampleNames`

parameter. It can plot null distribution(s) for a single
sample or multiple samples.

1 2 3 4 5 6 7 8 9 |

`permuteResult` |
A matrix, null distributions for each sample generated
using the |

`scoredf` |
A dataframe, singscores generated using the |

`pvals` |
A vector, estimated p-values using the |

`sampleNames` |
A character vector, sample IDs for which null distributions will be plotted |

`cutoff` |
numeric, the cutoff value for determining significance |

`textSize` |
numeric, size of axes labels, axes values and title |

`labelSize` |
numeric, size of label texts |

a ggplot object

Ruqian Lyu

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
ranked <- rankGenes(toy_expr_se)
scoredf <- simpleScore(ranked, upSet = toy_gs_up, downSet = toy_gs_dn)
# find out what backends can be registered on your machine
BiocParallel::registered()
# the first one is the default backend, and it can be changed explicitly.
permuteResult = generateNull(upSet = toy_gs_up, downSet = toy_gs_dn, ranked,
B =10, seed = 1,useBPPARAM = NULL)
# call the permutation function to generate the empirical scores
#for B times.
pvals <- getPvals(permuteResult,scoredf)
# plot for all samples
plotNull(permuteResult,scoredf,pvals,sampleNames = names(pvals))
#plot for the first sample
plotNull(permuteResult,scoredf,pvals,sampleNames = names(pvals)[1])
``` |

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