###############################################################################
#
# author: Christoph Kiefer
# email: christophak@bmb.sdu.dk
#
################################################################################
#'
#' Import Cq Values Calculated Using LightCycler Software
#'
#' @param file A txt file with calculated Cq values from the LightCycler software
#' @param scheme A pipetting scheeme, e.g., generated by get.pipettingScheme.
#' Generally a data.frame containing gene, cond, col and row information.
#'
#' @import readr
#' @import dplyr
#'
#' @examples scheme <- get.pipettingScheme(paste("primer", 1:7), c(1:5), 1, 2, 1, nrow = 10, first_col = 18)
#' import.LCcq("data-raw/primer.txt", scheme, decimal_mark = ',')
#'
#' @export
import.LCcq <- function(file, pipettingScheme = NULL, decimal_mark = '.') {
df <- read_tsv(file, locale = locale(decimal_mark = decimal_mark), skip = 1,
col_types = cols(
Include = col_character(),
Color = col_integer(),
Pos = col_character(),
Name = col_character(),
Cp = col_double(),
Concentration = col_character(),
Standard = col_integer(),
Status = col_character())) %>%
dplyr::select(cq = Cp, Pos) %>%
mutate(col = as.integer(substr(Pos, 2, nchar(Pos))),
row = substr(Pos, 1, 1)) %>%
dplyr::select(-Pos)
if (is.null(pipettingScheme)) {
return(df)
} else {
pipettingScheme %>%
left_join(df, by = c("col", "row"))
}
}
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