Description Author(s) Examples
ahp_plot is a slot of pipelineObj class. It consists of a matrix of problem hierarchy.
Daryanaz Dargahi <daryanazdargahi@gmail.com>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | 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)
|
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"
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