sim_pants: Simulate 'pants' to estimate size & power
In jdreyf/PANTS: Pathway analysis via network smoothing

Simulate pants to estimate size (effect=0) & power (effect>0) with score_fcn=identity vs. H1: "greater". Does not support type=="mediation".

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sim_pants(Gmat, phenotype, type = c("contrasts", "correlation"),
  effect.v = c(0, 0.2), alpha = 0.05, nsim = 10^3, nperm = 10^3,
  ncores = 1, seed = 1, verbose = TRUE, ker = NULL)

`Gmat`	Binary feature (e.g. gene) by pathway inclusion matrix, indicating which features are in which pathways.
`phenotype`	Vector of sample characteristics (correlation: numeric; contrasts: character). Should be same length as `ncol(object)`.
`type`	Type of ezlimma analysis per feauture; must be one of"contrasts" (`limma_contrasts`), "correlation" (`limma_cor`), or "mediation" (`hitman`). You can specify just the initial letter.
`effect.v`	Numeric vector of log fold-changes or percent of phentotypes to add.
`alpha`	Alpha level.
`nsim`	Number of simulations.
`nperm`	Number of sample permutations to evaluate significance of pathways.
`ncores`	Integer. If > 1, number of cores to use for parallel computing. You can detect how many are available for your system using `detectCores`.
`seed`	Random seed.
`verbose`	Logical; should the number of simulations be printed every 100 simulations?
`ker`	Laplacian kernel matrix representing the interaction network.