## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(metapone) ## ----example input------------------------------------------------------------ data(pos) head(pos) ## ----example input second matrix---------------------------------------------- data(neg) head(neg) ## ----example load database---------------------------------------------------- data(hmdbCompMZ) head(hmdbCompMZ) ## ----example load pathway----------------------------------------------------- data(pa) head(pa) ## ----example adduct ions------------------------------------------------------ pos.adductlist = c("M+H", "M+NH4", "M+Na", "M+ACN+H", "M+ACN+Na", "M+2ACN+H", "2M+H", "2M+Na", "2M+ACN+H") neg.adductlist = c("M-H", "M-2H", "M-2H+Na", "M-2H+K", "M-2H+NH4", "M-H2O-H", "M-H+Cl", "M+Cl", "M+2Cl") ## ----example analysis, warning=FALSE------------------------------------------ dat <- list(pos, neg) type <- list("pos", "neg") # permutation test r<-metapone(dat, type, pa, hmdbCompMZ=hmdbCompMZ, pos.adductlist=pos.adductlist, neg.adductlist=neg.adductlist, p.threshold=0.05,n.permu=200,fractional.count.power=0.5, max.match.count=10, use.fgsea = FALSE) # GSEA type testing based on metabolites #r<-metapone(dat, type, pa, hmdbCompMZ=hmdbCompMZ, pos.adductlist=pos.adductlist, neg.adductlist=neg.adductlist, p.threshold=0.05,n.permu=100,fractional.count.power=0.5, max.match.count=10, use.fgsea = TRUE, use.meta = TRUE) # GSEA type testing based on features #r<-metapone(dat, type, pa, hmdbCompMZ=hmdbCompMZ, pos.adductlist=pos.adductlist, neg.adductlist=neg.adductlist, p.threshold=0.05,n.permu=100,fractional.count.power=0.5, max.match.count=10, use.fgsea = TRUE, use.meta = FALSE) hist(ptable(r)[,1]) ## ----example continued-------------------------------------------------------- selection<-which(ptable(r)[,1]<0.025) ptable(r)[selection,] ## ----example continued 2------------------------------------------------------ ftable(r)[which(ptable(r)[,1]<0.025 & ptable(r)[,2]>=2)] ## ----example visulization, warning=FALSE-------------------------------------- bbplot1d(r@test.result, 0.025) bbplot2d(r@test.result, 0.025)