hipathia: Computes the level of activation of the subpathways for each...

In martahidalgo/hipathia: HiPathia: High-throughput Pathway Analysis

Computes the level of activation of the subpathways for each of the samples

Description

#@importFrom igraph

Usage

hipathia(
  genes_vals,
  metaginfo,
  uni.terms = FALSE,
  GO.terms = FALSE,
  sel_assay = 1,
  decompose = FALSE,
  scale = TRUE,
  maxnum = 100,
  verbose = TRUE,
  tol = 1e-06,
  test = TRUE
)

Arguments

genes_vals	A SummarizedExperiment or matrix with the normalized expression values of the genes. Rows represent genes and columns represent samples. Rownames() must be accepted gene IDs.
metaginfo	Pathways object
sel_assay	Character or integer, indicating the assay to be processed in the SummarizedExperiment. Only applied if genes_vals is a SummarizedExperiment.Default is 1.
decompose	Boolean, whether to compute the values for the decomposed subpathways. By default, effector subpathways are computed.
scale	Boolean, whether to scale the values matrix to [0,1]. Default is TRUE.
maxnum	Number of maximum iterations when iterating the signal through the loops into the pathways
verbose	Boolean, whether to show details about the results of the execution of hipathia
tol	Tolerance for the difference between two iterations when iterating the signal through the loops into the pathways
test	Boolean, whether to test the input objects. Default is TRUE.

Value

A MultiAssayExperiment object with the level of activation of the subpathways from the pathways in pathigraphs for the experiment with expression values in genes_vals.

Examples

data(exp_data)
pathways <- load_pathways(species = "hsa", pathways_list = c("hsa03320",
"hsa04012"))
results <- hipathia(exp_data, pathways, verbose = TRUE)
## Not run: results <- hipathia(exp_data, pathways, decompose = TRUE,
verbose = FALSE)
## End(Not run)

martahidalgo/hipathia documentation built on Jan. 12, 2023, 1:44 p.m.