calc_corrstat: Calculate correlation matrices for metabolite groups
In USEPA/LUMA: LCMS-Based Untargeted Metabolomics Assistant

Description Usage Arguments Value Examples

Calculates the correlation matrices for metabolite groups based on the best feature within the group that belongs to the primary metabolite.

1	calc_corrstat(Sample.df, Peak.list, get.mg, BLANK, IonMode)

`Sample.df`	a data frame with class info as columns. Must contain a separate row entry for each unique sex/class combination. Must contain the columns `"Sex","Class","n","Endogenous"`.
`Peak.list`	a data frame from CAMERA that has been parsed. Should contain all output columns from XCMS and CAMERA, and additional columns from `match_Annotation()`, `calc_minfrac()` and either `parse_pos_results()` or `parse_neg_results()`.
`get.mg`	numerical vector of metabolite groups that have more than one feature
`BLANK`	a logical indicating whether blanks are being evaluated
`IonMode`	a character string defining the ionization mode. Must be one of `c("Positive","Negative")`.

Peak.list of class 'tbl_df','tbl' or 'data.frame' with variables as columns. Has all of the columns as the original data frame with one additional column "Correlation.stat"

library(LUMA)
if(require(lcmsfishdata, quietly = TRUE)) {
file <- system.file('extdata','CAMERA_objects_Pos.Rdata', package =
"lcmsfishdata") # is case sensitive on Linux
load(file)
pspec.length <- sapply(anposGa@pspectra, function(x) length(x))
get.mg <- which(pspec.length > 1)
file2 <- system.file('extdata','Sample_Class.txt', package = "LUMA") # is
# case sensitive on Linux
Sample.df <- read.table(file2, sep = "\t", header = TRUE) #Ignore Warning message
Peak.list <-  lcmsfishdata::Peaklist_Pos$input_parsed
test <- calc_corrstat(Sample.df = Sample.df, Peak.list = Peak.list,
get.mg = get.mg, BLANK = FALSE, IonMode = "Positive")
test[["Correlation.stat"]][11:23]
}