R/peakClass.R
In ZhuMSLab/MetDNA: MetDNA
#' @title peakInfo
#' @description The Peakinfo class is the S4 class for Peak annotation
#' information.
#' @slot name Peak name.
#' @slot mz Peak m/z.
#' @slot rt Peak rentention time (RT).
#' @slot ms2 MS/MS spectrum of peak.
#' @slot annotation Annotation information of peak. It is a list contains
#' different annotation result.
#' @name peakInfo-Class
#' @exportClass peakInfo
#' @author Xiaotao Shen
#' @export
setClass("peakInfo",
representation(name = "character",
mz = "numeric",
rt = "numeric",
ms2 = "data.frame",
annotation = "list")
# prototype(name = "M102T561",
# mz = 102.0897,
# rt = 560.593,
# ms2 = data.frame(
# mz = c(41.03722,42.03253,43.01675,43.04068,
# 43.05172,44.04867,56.04833,57.88836,
# 58.06352,58.40606,59.07152,61.02475,
# 70.05883,72.04043,74.09432,87.06190,
# 102.08545,219.80564,219.90548,220.13019,
# 220.52996,222.31249,223.11005,223.85028),
# intensity = c(73,122,261,49,49,73,24,49,5113,24,
# 381,24,24,24,24,24,24,24,24,
# 24,24,24,24,24),stringsAsFactors = FALSE),
# annotation = list(
# list(type = "seed",
# From = NA,
# From.peak = NA,
# to = "C00576",
# step = NA,
# level = 1,
# as.seed = FALSE,
# as.seed.round = NA,
# isotope = "[M]",
# addcut = "M+H",
# charge = 1,
# Formula = "C5H11NO",
# mz.error = 0,
# rt.error = 0,
# int.error = NA,
# ms2.sim = 1,
# score = 1
# )
# )
# )
)
#-----------------------------------------------------------------------------
setMethod(f = "show",
signature = "peakInfo",
definition = function(object) {
cat("Peak information\n")
cat("--------------\n")
cat("Peak name:", object@name)
cat("\n")
cat("mz:", object@mz)
cat("\n")
cat("rt:", object@rt)
cat("\n")
cat("MS/MS spectrum:", ifelse(nrow(object@ms2) > 0, "Yes\n", "No\n"))
# cat(ifelse(nrow(object@ms2) > 0, "Yes\n", "No\n"))
# format(object@ms2)
cat('\n')
cat("--------------\n")
cat("Annotation information\n")
cat("--------------\n")
if(length(object@annotation) == 0){
cat("No annotation.")
}else{
for(i in 1:length(object@annotation)){
cat("\n")
cat("Annotation:",i)
cat("\n")
cat("Type:", object@annotation[[i]]$type)
cat("\n")
cat("From:", object@annotation[[i]]$From)
cat("\n")
cat("From which peak:", object@annotation[[i]]$From.peak)
cat("\n")
cat("Step:", object@annotation[[i]]$step)
cat("\n")
cat("Annotation result (KEGG ID):", object@annotation[[i]]$to)
cat("\n")
cat("Annotation level:", object@annotation[[i]]$level)
cat("\n")
cat("Is seed or not:", object@annotation[[i]]$as.seed)
cat("\n")
cat("In which round as seed:", object@annotation[[i]]$as.seed.round)
cat("\n")
cat("Isotpe:", object@annotation[[i]]$isotope)
cat("\n")
cat("Adduct:", object@annotation[[i]]$adduct)
cat("\n")
cat("Charge:", object@annotation[[i]]$charge)
cat("\n")
cat("Formula:", object@annotation[[i]]$Formula)
cat("\n")
cat("m/z error (ppm):", object@annotation[[i]]$mz.error)
cat("\n")
cat("RT error:", object@annotation[[i]]$rt.error)
cat("\n")
cat("Intensity ratio error:", object@annotation[[i]]$int.error)
cat("\n")
cat("MS/MS similarity (dot product):", object@annotation[[i]]$ms2.sim)
cat("\n")
cat("Score:", object@annotation[[i]]$score)
cat("\n")
}
}
}
)
setGeneric(
name = "getInfo",
def = function(object,...) {
standardGeneric("getInfo")
}
)
setMethod(f = "getInfo",
signature = "peakInfo",
definition = function(object) {
name <- object@name
mz <- object@mz
rt <- object@rt
annotation <- object@annotation
if(length(annotation) == 1){
annotation <- unlist(annotation)
}else{
idx.max.score <- which.max(unlist(lapply(annotation, function(x) {x$score})))
annotation <- unlist(annotation[[idx.max.score]])
names(annotation)[14] <- "Score"
}
result <- c(name, mz, rt, annotation)
names(result)[1:3] <- c("name", "mz", "rt")
return(result)
}
)
setGeneric(
name = "filterPeak",
def = function(object,...) {
standardGeneric("filterPeak")
}
)
# title filterPeak
# description Filter peakInfo data.
# author Xiaotao Shen
# \email{shenxt@@sioc.ac.cn}
# param object peakInfo data.
# param score.thr Score cutoff.
# return peakInfo data.
setMethod(f = "filterPeak",
signature = "peakInfo",
definition = function(object,
score.thr = 0) {
annotation <- object@annotation
if(length(annotation) != 0){
score <- unlist(lapply(annotation, function(x) {x$score}))
annotation <- annotation[order(score, decreasing = TRUE)]
score <- unlist(lapply(annotation, function(x) {x$score}))
if(length(which(score >= score.thr)) > 0){
annotation <- annotation[which(score >= score.thr)]
object@annotation <- annotation
}else{
object@annotation <- list()
}
}
return(object)
}
)
#' @title equalPeakinfo
#' @description Compare two peakInfo data.
#' @author Xiaotao Shen
#' \email{shenxt@@sioc.ac.cn}
#' @param object1 peakInfo.
#' @param object2 peakInfo.
#' @return TRUE or FALSE.
#' @export
setGeneric(name = "equalPeakinfo",
def = function(object1,
object2) {
name1 <- object1@name
mz1 <- object1@mz
rt1 <- object1@rt
annotation1 <- object1@annotation
name2 <- object2@name
mz2 <- object2@mz
rt2 <- object2@rt
annotation2 <- object2@annotation
if(length(annotation1) != length(annotation2)){
return(FALSE)
}
if(name1 == name2 & mz1 == mz2 & rt1 == rt2){
if(length(annotation1) == 0){
return(TRUE)
}else{
anno1 <- unlist(annotation1)
anno2 <- unlist(annotation2)
anno1 <- anno1[!is.na(anno1)]
anno2 <- anno2[!is.na(anno2)]
if(all(anno1 == anno2)){
return(TRUE)
}else{
return(FALSE)
}
}
}else{
return(FALSE)
}
})
#' @title equalPeakinfo1
#' @description Compare two tags2 data.
#' @author Xiaotao Shen
#' \email{shenxt@@sioc.ac.cn}
#' @param x The tags2 data.
#' @param y The tags2 data.
#' @return TRUE or FALSE.
#' @export
setGeneric(name = "equalPeakinfo1",
def = function(x,y){
result <-
mapply(function(x,y){equalPeakinfo(x, y)}, x, y)
result
})
# dataInfo: Data information
#
# description The data inforamtion class is the S4 class for metabolomics
# information.
# slot name Peak name.
# slot mz Peak m/z.
# slot rt Peak rentention time (RT).
# slot ms2 MS/MS spectrum of peak.
# slot annotation Annotation information of peak. It is a list contains
# different annotation result.
# name dataInfo-Class
# exportClass dataInfo
# author Xiaotao Shen
# export
# setClass("dataInfo",
# representation(sample.name = "character",
# peak.name = "character",
# sample.group = "list",
# sample.batch = "list",
# sample.data = "data.frame",
# sample.pheno = "data.frame",
# peak.tags = "data.frame")
# )
#
#
#
# setGeneric(name = "readData",
# def = function(sample = "sample.csv",
# tags = "tags.csv",
# info = "info.csv",
# pheno = NULL){
# sample <- readr::read_csv(sample, progress = FALSE, col_types = readr::cols())
# tags <- readr::read_csv(tags, progress = FALSE, col_types = readr::cols())
# info <- readr::read_csv(info, progress = FALSE, col_types = readr::cols())
#
# if(is.null(pheno)){
# sample.pheno <- data.frame()
# }else{
# sample.pheno <- readr::read_csv(pheno, progress = FALSE, col_types = readr::cols())
# }
#
# sample.name1 <- colnames(sample)
# sample.name2 <- info$sample.name
# if(any(sort(sample.name1) != sort(sample.name2))) {
# stop("Sample names from sample are different with sample names
# which are provided in info.")
# }
#
# sample <- sample[,order(sample.name2)]
# sample.name <- sample.name2
# peak.name <- tags$Peak.name
#
# sample.group <- info$group
# unique.sample.group <- unique(sample.group)
# sample.group <-
# lapply(unique.sample.group, function(x) {sample.name[which(info$group == x)]})
# names(sample.group) <- unique.sample.group
#
# sample.batch <- info$batch
# unique.sample.batch <- unique(sample.batch)
# sample.batch <-
# lapply(unique.sample.batch, function(x) {sample.name[which(info$batch == x)]})
# names(sample.batch) <- unique.sample.batch
#
# sample.data <- as.data.frame(sample)
#
# peak.tags <- as.data.frame(tags)
#
# dataInfo <- new(Class = "dataInfo",
# sample.name = sample.name,
# peak.name = peak.name,
# sample.group = sample.group,
# sample.batch = sample.batch,
# sample.data = sample.data,
# sample.pheno = sample.pheno,
# peak.tags = peak.tags)
# })
#
#
#
# setMethod(f = "show",
# signature = "dataInfo",
# definition = function(object) {
# cat("The data has",nrow(object@sample.data), "peaks and", ncol(object@sample.data), "samples\n")
# cat("(1) Sample information\n")
# cat("--------------\n")
# cat("Sample has", length(object@sample.group), "groups:\n")
# cat(names(object@sample.group))
# cat("\n")
# cat("Sample has", length(object@sample.batch), "batches.\n")
#
# cat("Sample names are",
# object@sample.name[ifelse(length(object@sample.name) > 5,
# list(c(1:5)),
# list(1:length(object@sample.name)))[[1]]])
# if(length(object@sample.name) > 5){
# cat("...")
# }
# cat("\n")
# if(nrow(object@sample.pheno) == 0){
# cat("There are not sample pheno information.\n")
# }else{
# cat("The sample pheno contains:\n")
# cat(colnames(sample.pheno))
# }
# cat("\n")
# cat("(2) Peak information\n")
# cat("--------------\n")
# cat("The peak information contains:\n")
# cat(colnames(peak.tags))
# }
# )
#
# setGeneric(
# name = "tTest",
# def = function(object,...) {
# standardGeneric("tTest")
# }
# )
#
# setMethod(f = "tTest",
# signature = "dataInfo",
# definition = function(object,
# group = c("W03", "W30"),
# adjust = TRUE,
# method = c("holm", "hochberg",
# "hommel", "bonferroni", "BH", "BY",
# "fdr", "none"),
# alternative = c("two.sided", "less", "greater"),
# mu = 0, paired = FALSE, var.equal = FALSE,
# conf.level = 0.95, ...){
# method = match.arg(method)
# alternative = match.arg(alternative)
# sample <- object@sample.data
# group <- object@sample.group[group]
# group1 <- sample[,group[[1]]]
# group2 <- sample[,group[[2]]]
#
# group1 <- apply(group1, 1, list)
# group1 <- lapply(group1, function(x) x[[1]])
#
# group2 <- apply(group2, 1, list)
# group2 <- lapply(group2, function(x) x[[1]])
#
# p.value <- mapply(function(x, y) {t.test(x, y)$p.value}, x = group1, y = group2)
# if(adjust){
# p.value <- p.adjust(p = p.value, method = method)
# }
# peak.name <- object@peak.tags$Peak.name
# names(p.value) <- peak.name
# return(p.value)
# })
# setGeneric(
# name = "foldChange",
# def = function(object,...) {
# standardGeneric("foldChange")
# }
# )
#
# setMethod(f = "foldChange",
# signature = "dataInfo",
# definition = function(object,
# group = c("W03", "W30"),
# method = c("median", "mean")){
# method = match.arg(method)
# sample <- object@sample.data
# group <- object@sample.group[group]
# group1 <- sample[,group[[1]]]
# group2 <- sample[,group[[2]]]
#
# group1 <- apply(group1, 1, method)
# group2 <- apply(group2, 1, method)
#
# fc <- group2/group1
# fc[is.nan(fc)] <- 1
# fc[is.infinite(fc)] <- max(fc[!is.infinite(fc)])
# fc[fc==0] <- min(fc[fc!=0])
#
# peak.name <- object@peak.tags$Peak.name
# names(fc) <- peak.name
# return(fc)
# })
ZhuMSLab/MetDNA documentation built on March 29, 2022, 5:45 p.m.
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#' @title peakInfo
#' @description The Peakinfo class is the S4 class for Peak annotation
#' information.
#' @slot name Peak name.
#' @slot mz Peak m/z.
#' @slot rt Peak rentention time (RT).
#' @slot ms2 MS/MS spectrum of peak.
#' @slot annotation Annotation information of peak. It is a list contains
#' different annotation result.
#' @name peakInfo-Class
#' @exportClass peakInfo
#' @author Xiaotao Shen
#' @export
setClass("peakInfo",
representation(name = "character",
mz = "numeric",
rt = "numeric",
ms2 = "data.frame",
annotation = "list")
# prototype(name = "M102T561",
# mz = 102.0897,
# rt = 560.593,
# ms2 = data.frame(
# mz = c(41.03722,42.03253,43.01675,43.04068,
# 43.05172,44.04867,56.04833,57.88836,
# 58.06352,58.40606,59.07152,61.02475,
# 70.05883,72.04043,74.09432,87.06190,
# 102.08545,219.80564,219.90548,220.13019,
# 220.52996,222.31249,223.11005,223.85028),
# intensity = c(73,122,261,49,49,73,24,49,5113,24,
# 381,24,24,24,24,24,24,24,24,
# 24,24,24,24,24),stringsAsFactors = FALSE),
# annotation = list(
# list(type = "seed",
# From = NA,
# From.peak = NA,
# to = "C00576",
# step = NA,
# level = 1,
# as.seed = FALSE,
# as.seed.round = NA,
# isotope = "[M]",
# addcut = "M+H",
# charge = 1,
# Formula = "C5H11NO",
# mz.error = 0,
# rt.error = 0,
# int.error = NA,
# ms2.sim = 1,
# score = 1
# )
# )
# )
)
#-----------------------------------------------------------------------------
setMethod(f = "show",
signature = "peakInfo",
definition = function(object) {
cat("Peak information\n")
cat("--------------\n")
cat("Peak name:", object@name)
cat("\n")
cat("mz:", object@mz)
cat("\n")
cat("rt:", object@rt)
cat("\n")
cat("MS/MS spectrum:", ifelse(nrow(object@ms2) > 0, "Yes\n", "No\n"))
# cat(ifelse(nrow(object@ms2) > 0, "Yes\n", "No\n"))
# format(object@ms2)
cat('\n')
cat("--------------\n")
cat("Annotation information\n")
cat("--------------\n")
if(length(object@annotation) == 0){
cat("No annotation.")
}else{
for(i in 1:length(object@annotation)){
cat("\n")
cat("Annotation:",i)
cat("\n")
cat("Type:", object@annotation[[i]]$type)
cat("\n")
cat("From:", object@annotation[[i]]$From)
cat("\n")
cat("From which peak:", object@annotation[[i]]$From.peak)
cat("\n")
cat("Step:", object@annotation[[i]]$step)
cat("\n")
cat("Annotation result (KEGG ID):", object@annotation[[i]]$to)
cat("\n")
cat("Annotation level:", object@annotation[[i]]$level)
cat("\n")
cat("Is seed or not:", object@annotation[[i]]$as.seed)
cat("\n")
cat("In which round as seed:", object@annotation[[i]]$as.seed.round)
cat("\n")
cat("Isotpe:", object@annotation[[i]]$isotope)
cat("\n")
cat("Adduct:", object@annotation[[i]]$adduct)
cat("\n")
cat("Charge:", object@annotation[[i]]$charge)
cat("\n")
cat("Formula:", object@annotation[[i]]$Formula)
cat("\n")
cat("m/z error (ppm):", object@annotation[[i]]$mz.error)
cat("\n")
cat("RT error:", object@annotation[[i]]$rt.error)
cat("\n")
cat("Intensity ratio error:", object@annotation[[i]]$int.error)
cat("\n")
cat("MS/MS similarity (dot product):", object@annotation[[i]]$ms2.sim)
cat("\n")
cat("Score:", object@annotation[[i]]$score)
cat("\n")
}
}
}
)
setGeneric(
name = "getInfo",
def = function(object,...) {
standardGeneric("getInfo")
}
)
setMethod(f = "getInfo",
signature = "peakInfo",
definition = function(object) {
name <- object@name
mz <- object@mz
rt <- object@rt
annotation <- object@annotation
if(length(annotation) == 1){
annotation <- unlist(annotation)
}else{
idx.max.score <- which.max(unlist(lapply(annotation, function(x) {x$score})))
annotation <- unlist(annotation[[idx.max.score]])
names(annotation)[14] <- "Score"
}
result <- c(name, mz, rt, annotation)
names(result)[1:3] <- c("name", "mz", "rt")
return(result)
}
)
setGeneric(
name = "filterPeak",
def = function(object,...) {
standardGeneric("filterPeak")
}
)
# title filterPeak
# description Filter peakInfo data.
# author Xiaotao Shen
# \email{shenxt@@sioc.ac.cn}
# param object peakInfo data.
# param score.thr Score cutoff.
# return peakInfo data.
setMethod(f = "filterPeak",
signature = "peakInfo",
definition = function(object,
score.thr = 0) {
annotation <- object@annotation
if(length(annotation) != 0){
score <- unlist(lapply(annotation, function(x) {x$score}))
annotation <- annotation[order(score, decreasing = TRUE)]
score <- unlist(lapply(annotation, function(x) {x$score}))
if(length(which(score >= score.thr)) > 0){
annotation <- annotation[which(score >= score.thr)]
object@annotation <- annotation
}else{
object@annotation <- list()
}
}
return(object)
}
)
#' @title equalPeakinfo
#' @description Compare two peakInfo data.
#' @author Xiaotao Shen
#' \email{shenxt@@sioc.ac.cn}
#' @param object1 peakInfo.
#' @param object2 peakInfo.
#' @return TRUE or FALSE.
#' @export
setGeneric(name = "equalPeakinfo",
def = function(object1,
object2) {
name1 <- object1@name
mz1 <- object1@mz
rt1 <- object1@rt
annotation1 <- object1@annotation
name2 <- object2@name
mz2 <- object2@mz
rt2 <- object2@rt
annotation2 <- object2@annotation
if(length(annotation1) != length(annotation2)){
return(FALSE)
}
if(name1 == name2 & mz1 == mz2 & rt1 == rt2){
if(length(annotation1) == 0){
return(TRUE)
}else{
anno1 <- unlist(annotation1)
anno2 <- unlist(annotation2)
anno1 <- anno1[!is.na(anno1)]
anno2 <- anno2[!is.na(anno2)]
if(all(anno1 == anno2)){
return(TRUE)
}else{
return(FALSE)
}
}
}else{
return(FALSE)
}
})
#' @title equalPeakinfo1
#' @description Compare two tags2 data.
#' @author Xiaotao Shen
#' \email{shenxt@@sioc.ac.cn}
#' @param x The tags2 data.
#' @param y The tags2 data.
#' @return TRUE or FALSE.
#' @export
setGeneric(name = "equalPeakinfo1",
def = function(x,y){
result <-
mapply(function(x,y){equalPeakinfo(x, y)}, x, y)
result
})
# dataInfo: Data information
#
# description The data inforamtion class is the S4 class for metabolomics
# information.
# slot name Peak name.
# slot mz Peak m/z.
# slot rt Peak rentention time (RT).
# slot ms2 MS/MS spectrum of peak.
# slot annotation Annotation information of peak. It is a list contains
# different annotation result.
# name dataInfo-Class
# exportClass dataInfo
# author Xiaotao Shen
# export
# setClass("dataInfo",
# representation(sample.name = "character",
# peak.name = "character",
# sample.group = "list",
# sample.batch = "list",
# sample.data = "data.frame",
# sample.pheno = "data.frame",
# peak.tags = "data.frame")
# )
#
#
#
# setGeneric(name = "readData",
# def = function(sample = "sample.csv",
# tags = "tags.csv",
# info = "info.csv",
# pheno = NULL){
# sample <- readr::read_csv(sample, progress = FALSE, col_types = readr::cols())
# tags <- readr::read_csv(tags, progress = FALSE, col_types = readr::cols())
# info <- readr::read_csv(info, progress = FALSE, col_types = readr::cols())
#
# if(is.null(pheno)){
# sample.pheno <- data.frame()
# }else{
# sample.pheno <- readr::read_csv(pheno, progress = FALSE, col_types = readr::cols())
# }
#
# sample.name1 <- colnames(sample)
# sample.name2 <- info$sample.name
# if(any(sort(sample.name1) != sort(sample.name2))) {
# stop("Sample names from sample are different with sample names
# which are provided in info.")
# }
#
# sample <- sample[,order(sample.name2)]
# sample.name <- sample.name2
# peak.name <- tags$Peak.name
#
# sample.group <- info$group
# unique.sample.group <- unique(sample.group)
# sample.group <-
# lapply(unique.sample.group, function(x) {sample.name[which(info$group == x)]})
# names(sample.group) <- unique.sample.group
#
# sample.batch <- info$batch
# unique.sample.batch <- unique(sample.batch)
# sample.batch <-
# lapply(unique.sample.batch, function(x) {sample.name[which(info$batch == x)]})
# names(sample.batch) <- unique.sample.batch
#
# sample.data <- as.data.frame(sample)
#
# peak.tags <- as.data.frame(tags)
#
# dataInfo <- new(Class = "dataInfo",
# sample.name = sample.name,
# peak.name = peak.name,
# sample.group = sample.group,
# sample.batch = sample.batch,
# sample.data = sample.data,
# sample.pheno = sample.pheno,
# peak.tags = peak.tags)
# })
#
#
#
# setMethod(f = "show",
# signature = "dataInfo",
# definition = function(object) {
# cat("The data has",nrow(object@sample.data), "peaks and", ncol(object@sample.data), "samples\n")
# cat("(1) Sample information\n")
# cat("--------------\n")
# cat("Sample has", length(object@sample.group), "groups:\n")
# cat(names(object@sample.group))
# cat("\n")
# cat("Sample has", length(object@sample.batch), "batches.\n")
#
# cat("Sample names are",
# object@sample.name[ifelse(length(object@sample.name) > 5,
# list(c(1:5)),
# list(1:length(object@sample.name)))[[1]]])
# if(length(object@sample.name) > 5){
# cat("...")
# }
# cat("\n")
# if(nrow(object@sample.pheno) == 0){
# cat("There are not sample pheno information.\n")
# }else{
# cat("The sample pheno contains:\n")
# cat(colnames(sample.pheno))
# }
# cat("\n")
# cat("(2) Peak information\n")
# cat("--------------\n")
# cat("The peak information contains:\n")
# cat(colnames(peak.tags))
# }
# )
#
# setGeneric(
# name = "tTest",
# def = function(object,...) {
# standardGeneric("tTest")
# }
# )
#
# setMethod(f = "tTest",
# signature = "dataInfo",
# definition = function(object,
# group = c("W03", "W30"),
# adjust = TRUE,
# method = c("holm", "hochberg",
# "hommel", "bonferroni", "BH", "BY",
# "fdr", "none"),
# alternative = c("two.sided", "less", "greater"),
# mu = 0, paired = FALSE, var.equal = FALSE,
# conf.level = 0.95, ...){
# method = match.arg(method)
# alternative = match.arg(alternative)
# sample <- object@sample.data
# group <- object@sample.group[group]
# group1 <- sample[,group[[1]]]
# group2 <- sample[,group[[2]]]
#
# group1 <- apply(group1, 1, list)
# group1 <- lapply(group1, function(x) x[[1]])
#
# group2 <- apply(group2, 1, list)
# group2 <- lapply(group2, function(x) x[[1]])
#
# p.value <- mapply(function(x, y) {t.test(x, y)$p.value}, x = group1, y = group2)
# if(adjust){
# p.value <- p.adjust(p = p.value, method = method)
# }
# peak.name <- object@peak.tags$Peak.name
# names(p.value) <- peak.name
# return(p.value)
# })
# setGeneric(
# name = "foldChange",
# def = function(object,...) {
# standardGeneric("foldChange")
# }
# )
#
# setMethod(f = "foldChange",
# signature = "dataInfo",
# definition = function(object,
# group = c("W03", "W30"),
# method = c("median", "mean")){
# method = match.arg(method)
# sample <- object@sample.data
# group <- object@sample.group[group]
# group1 <- sample[,group[[1]]]
# group2 <- sample[,group[[2]]]
#
# group1 <- apply(group1, 1, method)
# group2 <- apply(group2, 1, method)
#
# fc <- group2/group1
# fc[is.nan(fc)] <- 1
# fc[is.infinite(fc)] <- max(fc[!is.infinite(fc)])
# fc[fc==0] <- min(fc[fc!=0])
#
# peak.name <- object@peak.tags$Peak.name
# names(fc) <- peak.name
# return(fc)
# })
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