PAPi-package {PAPi} | R Documentation |
PAPi is an R package that implements the PAPi algorithm published in Aggio et al. 2010. It relates metabolite abundances to metabolic pathway activity. For this, PAPi uses a typical metabolomics data set and the KEGG (Kyoto Encyclopedia of Genes and Genomes) database (http://www.genome.jp/kegg/).
Package: | PAPi |
Type: | Package |
Version: | 0.99.3 |
Date: | 2013-03-27 |
License: | GPL(>= 2) |
PAPi has five functions: buildDatabase
, addKeggCodes
, papi
, papiHtest
and papiLine
. The main function of PAPi is papi, which uses a metabolomics data set for predicting the activity of metabolic pathways. For this, papi requires the name of each compound to be substituted by its respective KEGG code. KEGG code is a unique compound identifier in KEGG database. The function addKeggCodes then automatically substitutes compounds names by their respective KEGG codes while papi generates a list of metabolic pathways with their predicted metabolic activity. papiHtest performs ANOVA or t-test on results generated by papi. Finally, papiLine generates a line graph of results produced by papi or papiHtest.
Raphael Aggio Maintainer: Raphael Aggio (raphael.aggio@gmail.com)
Aggio, R.B.M; Ruggiero, K. and Villas-Boas, S.G. (2010) - Pathway Activity Profiling (PAPi): from metabolite profile to metabolic pathway activity. Bioinformatics.
### Building input data #### Names <- c("Replicates", "C00197", "C05345", "C00031", "C00118", "C00111") Sample1 <- c("cond1", 0.2, 0.3, 0.8, 1.1, 1.2) Sample2 <- c("cond1", 0.3, 0.2, 0.6, 1.5, 1.5) Sample3 <- c("cond1", 0.5, 0.4, 0.7, 1.2, 1.3) Sample4 <- c("cond2", 1.1, 0.6, 1.2, NA, 0.2) Sample5 <- c("cond2", 1.0, 0.7, 1.1, NA, 0.3) Sample6 <- c("cond2", 0.9, 0.7, 1.5, NA, 0.2) papiData <- data.frame(cbind(Names, Sample1, Sample2, Sample3, Sample4, Sample5, Sample6), stringsAsFactors = FALSE) ### Applying papi #### #papiResults <- papi(papiData, save = FALSE)