calcul_e {TTMap} | R Documentation |
Calculation of the value of epsilon
calcul_e(dd5, pvalcutoff = 0.95, tt1, alpha = 1, S = colnames(tt1$Normal.mat)) calcul_e_single(dd5, pvalcutoff = 0.95, tt1, alpha = 1, S = colnames(tt1$Normal.mat))
dd5 |
distance matrix as created by |
pvalcutoff |
cutoff of 0.05 percent (default) or less |
tt1 |
output of |
alpha |
a cutoff value for the FC between the group of control and the disease group |
S |
subset of columns to be considered |
al |
number representing the cutoff to choose for the relatedness with dd5 |
Rachel Jeitziner
control_adjustment
,
hyperrectangle_deviation_assessment
,
ttmap_sgn_genes
,
generate_mismatch_distance
##-- library(airway) data(airway) airway <- airway[rowSums(assay(airway))>80,] assay(airway) <- log(assay(airway)+1,2) ALPHA <- 1 the_experiment <- TTMap::make_matrices(airway, seq_len(4), seq_len(4) + 4, rownames(airway), rownames(airway)) TTMAP_part1prime <-TTMap::control_adjustment( normal.pcl = the_experiment$CTRL, tumor.pcl = the_experiment$TEST, normalname = "The_healthy_controls", dataname = "Effect_of_cancer", org.directory = tempdir(), e = 0, P = 1.1, B = 0); Kprime <- 4; TTMAP_part1_hda <- TTMap::hyperrectangle_deviation_assessment(x = TTMAP_part1prime, k = Kprime,dataname = "Effect_of_cancer", normalname = "The_healthy_controls"); annot <- c(paste(colnames( the_experiment$TEST[,-(seq_len(3))]), "Dis", sep = "."), paste(colnames(the_experiment$CTRL[, -seq_len(3)]), "Dis", sep = ".")) dd5_sgn_only <-TTMap::generate_mismatch_distance( TTMAP_part1_hda, select=rownames(TTMAP_part1_hda$Dc.Dmat), alpha = ALPHA) e <- TTMap::calcul_e(dd5_sgn_only, 0.95, TTMAP_part1prime, 1)