pipeline

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Description

a pipeline for prioritization estimation using analytic hierarchy process (AHP), which supports both relative and rating AHP models.

Usage

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pipeline(srcfile, model, simulation = 500)

Arguments

srcfile

a character matrix, where the first column specifies the hierarchy order, the second column includes elements IDs, and the third column includes the path to the PCM/priority matrices (See the example below).

model

the AHP computation model. Choose from relative and rating models. If using the relative model pairwise comparison matrices must be provided for the evaluation of alternatives. However, if using the raing model, rating matrices must be provided for the evaluation of alternatives.

simulation

simulation size for computation of Saaty's inconsistency

Value

An S4 object including the ahp wight and consistancy measures, and data structures to visualize with ahplot(), rainbowplot(), and wplot().

Author(s)

Daryanaz Dargahi

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)

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