Nothing
#'Make a target table for adductomicsR quantificaton using
#'specSimPep results
#'@param allresultsFile character a full path to the allResults
#'file generated by specSimPepId
#'@param csvDir character a full path to a directory to save the
#'csv file to
#'output is a csv file called targTable.csv which can be used
#'in the adductQuant function
#'@examples
#'generateTargTable(paste0(system.file("extdata",package="adductomicsR"),
#''/allResults_ALVLIAFAQYLQQCPFEDHVK_example.csv'),csvDir=getwd())
#'@usage generateTargTable(allresultsFile = NULL, csvDir = NULL)
#'@return cvs file
#'@export
generateTargTable <-
function(allresultsFile = NULL,
csvDir = NULL) {
MIM = NULL
adjMIM = NULL
RT = NULL
adjRT = NULL
MSMSGroupsName = NULL
data = read.csv(allresultsFile, sep = ",", header = TRUE)
groups = unique(data$MSMSGroupsName)
# obtain unique groups with average RT and MIM
data2 <-
data.frame(
dplyr::summarise(
dplyr::group_by(data, MSMSGroupsName),
MIM = mean(MIM),
adjMIM <- mean(adjMIM),
RT = mean(RT),
adjRT = mean(adjRT)
)
)
data2 <- data2[-(nrow(data2)),]
# create a target table based on the non adjusted results
targ <- data.frame(
mass = data2$MIM,
RT = data2$RT,
peptide = rep("ALVLIAFAQYLQQCPFEDHVK",
length(nrow(data2))),
chargeState = rep(3, length(nrow(data2)))
)
hk <-
data.frame(
mass = 575.31113,
RT = 13.55,
peptide = "LVNEVTEFAK",
chargeState = 2
)
targetTable <- rbind(hk, targ)
write.table(
targetTable,
file = paste0(csvDir, "/targTable.csv"),
sep = ",",
quote = FALSE,
row.names = FALSE
)
}
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