quantify_terms: Computes the level of activation of the functions related to...
In hipathia: HiPathia: High-throughput Pathway Analysis

Description Usage Arguments Value Examples

Computes the level of activation of the functions related to the previously computed subpathways

1 2	quantify_terms(results, metaginfo, dbannot, out_matrix = FALSE, normalize = TRUE)

`results`	List of results as returned by the `hipathia` function
`metaginfo`	Pathways object
`dbannot`	Either a string indicating which precomputed annotation to use ("uniprot" for Uniprot Keywords or "GO" for Gene Ontology terms), or a dataframe with the annotation of the genes to the functions. First column are gene symbols, second column the functions.
`out_matrix`	Boolean, whther the output object should be a matrix object. Default is FALSE, returning a SummarizedExperiment object.
`normalize`	Boolean, whether to normalize the matrix of pathway values with `normalize_paths` before quantifying the signal. Due to the nature of the Hipathia method, in which the length of each pathway may alter its signal rank, we strongly recommend to perform this normalization. This normalization removes the bias. Default is set to TRUE.

Matrix with the level of activation of the functions in dbannot

data(results)
pathways <- load_pathways(species = "hsa", pathways_list = c("hsa03320",
"hsa04012"))
go_values <- quantify_terms(results, pathways, "GO")
uniprot_values <- quantify_terms(results, pathways, "uniprot")