calc_PFP_score {PFP} | R Documentation |
It can evaluate the performance of a gene list in the pathway networks.
calc_PFP_score( genes, PFPRefnet, lambda = 0.5, coeff1 = 1, coeff2 = 0.1, statistic = TRUE, bg_genelist = NULL, adjust_method = "BH" )
genes, |
a vector of characters |
PFPRefnet, |
A PFPRefnet class |
lambda, |
a numeric, the coefficient for keeping balance between the node_score and edge_score in PFP model |
coeff1, |
a numeric, the weight coefficient for directly connected score in PFP model |
coeff2, |
a numeric, the weight coefficient for indirectly connected score in PFP model |
statistic, |
a logical,whether to do the statistical test |
bg_genelist, |
a vector of characters, background gene set for the statistical test |
adjust_method, |
statistic test method for adjust the p_value. It could be "holm", "hochberg", "hommel", "bonferroni", "BH", "BY","fdr", "none". |
The main part of pathway fingerprint. PFP is used to evaluate the performance of a gene_list in some pathway networks by considering the genes' topological location in a pathway. Then we can get every gene's score and the pathway score is caculated by sum all genes' score. All pathways' scores combine the pathway fingerprint.
The score of PFP
data(gene_list_hsa) data(PFPRefnet_hsa) PFP <- calc_PFP_score(gene_list_hsa,PFPRefnet_hsa)