ahp_plot: AHP plot slot

Description Author(s) Examples

Description

ahp_plot is a slot of pipelineObj class. It consists of a matrix of problem hierarchy.

Author(s)

Daryanaz Dargahi <[email protected]>

Examples

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mat <- matrix(nrow = 7, ncol = 3, data = NA)
mat[,1] <- c('0', '1','2','3','4','4.1','4.2')
mat[,2] <- c('Prioritization_of_DE_genes','Tumor_expression','Normal_expression',
             'Frequency', 'Epitopes', 'Number_of_epitopes', 'Size_of_epitopes')
mat[,3] <- c(system.file('extdata','aggreg.judgement.tsv',package = 'Prize'),
             system.file('extdata','tumor.PCM.tsv',package = 'Prize'),
             system.file('extdata','normal.PCM.tsv',package = 'Prize'),
             system.file('extdata','freq.PCM.tsv',package = 'Prize'),
             system.file('extdata','epitope.PCM.tsv',package = 'Prize'),
             system.file('extdata','epitopeNum.PCM.tsv',package = 'Prize'),
             system.file('extdata','epitopeLength.PCM.tsv',package = 'Prize'))

result <- pipeline(mat, model = 'relative', simulation = 500)
ahp_plot(result)

Example output

0 Prioritization_of_DE_genes is processed.
1 Tumor_expression is processed.
2 Normal_expression is processed.
3 Frequency is processed.
4 Epitopes is processed.
4.1 Number_of_epitopes is processed.
4.2 Size_of_epitopes is processed.
     level ID                           Weight              
[1,] "0"   "Prioritization_of_DE_genes" NA                  
[2,] "1"   "Tumor_expression"           "0.469729767043589" 
[3,] "2"   "Normal_expression"          "0.340673842031607" 
[4,] "3"   "Frequency"                  "0.116001935957881" 
[5,] "4"   "Epitopes"                   "0.0735944549669227"
[6,] "4.1" "Number_of_epitopes"         "0.0091993044560472"
[7,] "4.2" "Size_of_epitopes"           "0.0643951505108755"

Prize documentation built on May 2, 2018, 3:13 a.m.