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#' Calculate Retention Time Consistency (of a Peak Group)
#'
#' Calculates the Retention Time Consistency of each chromatographic peak in a group of samples. For each sample, the Retention Time
#' Consistency is found by calculating the difference between the time at the center of the sample peak and the mean
#' time of all peak centers normalized by the mean time of all the peak centers.
#'
#' This function repurposed from TargetedMSQC. Toghi Eshghi, S., Auger, P., & Mathews, W. R. (2018). Quality assessment and
#' interference detection in targeted mass spectrometry data using machine learning. Clinical Proteomics, 15.
#' https://doi.org/10.1186/s12014-018-9209-x
#'
#' @param peakDataList A list of vectors containing characteristic information about a chromatographic peak - including the retention time range
#' @param ptsList A list of 2D matrices containing the retention time and intensity values of a chromatographic peak
#' @return The Retention Time Consistency of a Peak Group (double)
#'
#' @examples
#' # Calculate Retention Time Consistency for each peak
#' data(ex_ptsList)
#' data(ex_peakDataList)
#' rtc <- calculateRetentionTimeConsistency(peakDataList = ex_peakDataList, ptsList = ex_ptsList)
#'
#' @export
calculateRetentionTimeConsistency <- function(peakDataList, ptsList){
peakData <- peakDataList
pts <- ptsList
centers <- sapply(1:length(pts), function(i){
pd <- peakData[[i]]
pt <- pts[[i]]
peakrange <- pd[c("rtmin", "rtmax")]
ptsidx <- pt[, 1] >= peakrange[1] & pt[, 1] <= peakrange[2]
intPts <- pt[ptsidx, ]
if(length(intPts)>2){
time <- intPts[,1]
time_len <- length(time)
t_end <- time[time_len]
t_beg <- time[1]
center_time <- round(t_end - (abs(t_end-t_beg)/2),4)
}else{
center_time <- NA
}
return(center_time)
})
mean_center <- mean(centers, na.rm=T)
rt_diff <- abs(centers - mean_center) / mean_center
rt_consistency <- mean(rt_diff, na.rm=T)
return(rt_consistency)
}
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