Nothing
R/1.input_data.R
In dPCP: Automated Analysis of Multiplex Digital PCR Data
Defines functions
read_sample
read_reference
read_sampleTable
dbscan_combination
Documented in
dbscan_combination
read_reference
read_sample
read_sampleTable
#' Test eps and minPts combinations for DBSCAN analysis
#'
#' This function tests all combinations of eps and minPts for DBSCAN analysis
#' of reference samples indicated in refID. The results are represented in
#' scatterplots exported to a pdf file.
#' @inheritParams dPCP
#' @param refID a string or a character vector of chipID (Thermo Fisher) or
#' the complete file name with the extension (Bio-Rad) of reference sample(s)
#' to be analysed.
#' @param reference.quality numeric. Between 0 and 1. Quality threshold
#' to subset the data (just for Thermo Fisher). If different thresholds have
#' to be applied to various reference samples, a vectror of the same length
#' of \code{refID} has to be provided.
#' @param eps a numeric vector of values to be tested. Maximum distance
#' between elements within a cluster in a DBSCAN analysis.
#' See also \code{\link[dbscan]{dbscan}}.
#' @param minPts a numeric vector of values to be tested. Number of minimum
#' elements to assemble a cluster in a DBSCAN analysis.
#' See also \code{\link[dbscan]{dbscan}}.
#' @return A pdf file containing the scatterplots of DBSCAN analysis performed
#' with all combinations of eps and minPts.
#' Each reference generates a different pdf file.
#' @examples
#' \donttest{
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' dbscan_combination("dilution20200313_B01_Amplitude.csv",
#' file.location = fileLoc, system = "bio-rad",
#' eps = c(150, 160, 180, 190), minPts = c(80, 100, 120))
#'
#' unlink("dilution20200313_B01_Amplitude.pdf")
#' }
#' @export
dbscan_combination <- function(refID, system = NULL, file.location = ".",
reference.quality = 0.5,
eps = c(120, 150, 180, 200),
minPts = c(20, 50, 80, 100)) {
if (!is.character(refID))
stop("'refID' must be a character string or vector")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
reference.quality <- "Defined by Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
system <- "Other"
reference.quality <- "Defined by the supplier"
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if ((system == "Thermo Fisher") & (
!is.numeric(reference.quality) || any(reference.quality > 1) ||
any(reference.quality < 0)))
stop("Invalid value for 'reference.quality'. It must be between 0 and 1")
if ((system == "Thermo Fisher") & (
length(reference.quality) > 1 &
length(reference.quality) != length(unique(refID))))
stop("Invalid value for 'reference.quality'. It must be a numeric value or
a numeric vector of lenght equal to the number of reference samples")
if (!is.numeric(c(eps, minPts))) stop("'eps' and 'minPts' must be numeric")
#Calculate all combinations
combinations <- expand.grid(eps, minPts)
comb <- lapply(seq(length(refID)), function(x) {
if (system == "Thermo Fisher") {
#List reference experiment file
eds.file <- list.files(file.location,
pattern = paste(refID[x], ".eds", sep = ""))
if (length(eds.file) == 0)
stop(paste0("An experiment file of reference", " '", refID[x],
"'", " can not be found."))
if (length(eds.file) > 1)
stop(paste0("Multiple experiment files for reference", " '",
refID[x], "'."))
#Extract fluoresce and quality data
quality.value <- utils::read.csv(
unz(paste0(file.location, "/", eds.file),
"apldbio/sds/quality_metrics/QVhOverallScores.CSV"))
fluorescence <- utils::read.csv(
unz(paste0(file.location, "/", eds.file),
"apldbio/sds/quants_dye/ComponentData.CSV"))
reference.data <- matrix(c(
quality.value[, 1], fluorescence[, 3], fluorescence[, 1]), ncol = 3,
dimnames = list(1:nrow(quality.value), c("Quality", "Vic", "Fam")))
if (length(reference.quality) > 1) {
reference.quality <- reference.quality[x]
}
#Keep data with quality score higher than reference.quality
submatrix <- subset.matrix(
reference.data[, c(2, 3)], reference.data[, 1] >= reference.quality)
if (nrow(submatrix) < 10000)
stop(paste0("The number of wells qualified by reference.quality is less
than 10000 for reference ", "'", refID[x], "'.", "
Try to reduce the quality threshold or run another chip"))
} else {
ref.file <- list.files(file.location, pattern = refID[x])
if (length(ref.file) == 0)
stop(paste0("No file of reference", " '", refID[x], "'",
" can be found."))
if (length(ref.file) > 1)
stop(paste0("Multiple files for reference", " '", refID[x], "'."))
if (stringr::str_sub(ref.file, start = -4) == ".csv") {
#If it is a `.csv` file, extract fluorescence and quality data
fluorescence <- utils::read.csv(
paste0(file.location, "/", ref.file), na.strings = c("NA", ""),
colClasses = c("numeric", "numeric", "NULL"))
submatrix <- matrix(c(fluorescence[,2],fluorescence[,1]), ncol = 2)
colnames(submatrix) <- c("Vic", "Fam")
}
}
#Try all combinations and plot the results
graph.comb <- lapply(seq(nrow(combinations)), function(y) {
dbclus <- dbscan::dbscan(submatrix, combinations[y, 1],
combinations[y, 2])
p <- ggplot(as.data.frame(submatrix), aes_string(x = "Vic", y = "Fam")) +
geom_point(size = 0.5, aes(color = factor(dbclus$cluster))) +
geom_point(size = 0.5,
data = as.data.frame(submatrix)[dbclus$cluster == 0, ],
aes_string(x = "Vic", y = "Fam"), colour = "grey40") +
labs(title = paste0("eps = ", dbclus$eps, ", minPts = ",
dbclus$minPts)) +
theme(
panel.background = element_rect(fill = "white"),
panel.border = element_rect(fill = NA, color = "black"),
legend.position = "none",
plot.title = element_text(size = 14),
axis.title.x = element_text(size = 12),
axis.title.y = element_text(size = 12),
axis.text = element_text(size = 9)
)
})
#Draw 4 plots per page and export to pdf
tot <- ggpubr::ggarrange(plotlist = graph.comb, ncol = 2, nrow = 2)
if (system == "Thermo Fisher") {
ggpubr::ggexport(tot, filename = paste0(refID[x], ".pdf"))
} else {
ggpubr::ggexport(
tot,
filename = paste0(stringr::str_sub(refID[x], end = -5), ".pdf"))
}
})
}
#' Read sample table
#'
#' This function reads a file containing the essential information about the
#' samples and experimental settings. The file has to be filled out by the user
#' and formatted as described in the vignette.
#' @inheritParams dPCP
#' @return An object of class \code{sample_table}.
#' @examples
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' #Read sample table file
#' sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
#' file.location = fileLoc)
#' @export
read_sampleTable <- function(file, system = NULL, file.location = ".") {
if (!is.character(file)) stop("'file' must be a character string")
if (stringr::str_sub(file, start = -4) != ".csv")
stop("'file' must be a '.csv' file. Please use the template provided.")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
system <- "Other"
reference.quality <- "Defined by the supplier"
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if (!is.character(file.location))
stop("'file.location' must be a path name indicating reference and
sample files location")
sample.table <- utils::read.csv(file,
stringsAsFactors = FALSE,
na.strings = c("NA", ""))
if (ncol(sample.table) != 9)
stop("Columns number is not correct. Please use the template provided.")
if (any(colnames(sample.table) !=
c("Sample.name", "Chip.ID.Well.ID", "No.of.targets", "FAM.target",
"Target.3", "Target.4", "VIC.HEX.target", "Reference",
"Dilution")) ||
any(is.na(colnames(sample.table))))
stop("Columns names are not correct. Please use the template provided.")
if (any(grepl(",", sample.table))) {
new.col <- lapply(sample.table[, c(1, 4:7)], function(x) {
x <- gsub(",", ".", x)
})
sample.table[, c(1, 4:7)] <- new.col
}
if (any(is.na(sample.table$Sample.name))) {
na.names <- sapply(which(is.na(sample.table$Sample.name)), function(x) {
paste0("Sample", x)
})
sample.table$Sample.name[which(is.na(sample.table$Sample.name))] <-
na.names
}
if (any(is.na(sample.table$Chip.ID.Well.ID)))
stop("Sample Chip or Well ID must be provided")
if (!is.integer(sample.table$No.of.targets) ||
any(is.na(sample.table$No.of.targets)) ||
any(sample.table$No.of.targets > 4) ||
any(sample.table$No.of.targets < 1))
stop("Invalid value for No of targets")
if (any(duplicated(sample.table$Sample.name)) &&
any(duplicated(sample.table$Sample.name) !=
duplicated(paste(sample.table$Sample.name,
sample.table$No.of.targets,"_"))))
stop("Replicates must have the same number of targets")
if (any(is.na(sample.table$Reference))) {
ref <- lapply(which(is.na(sample.table$Reference)), function(x) {
if (system == "Thermo Fisher") {
ref.file <- sample.table$Chip.ID.Well.ID[x]
} else {
ref.file <- list.files(
file.location,
pattern = paste0(as.character(sample.table$Chip.ID.Well.ID[x]),
"_Amplitude.csv"))
}
if (length(ref.file) > 1) {
stop(paste0("More than one file has been found for the sample ",
sample.table$Chip.ID.Well.ID[x]))
} else if (length(ref.file) == 0)
stop(paste0("No file has been found for the sample ",
sample.table$Chip.ID.Well.ID[x]))
ref.file
})
sample.table$Reference[which(is.na(sample.table$Reference))] <-
unlist(ref)
}
if (!is.numeric(sample.table$Dilution) ||
any(is.na(sample.table$Dilution)) ||
any(sample.table$Dilution > 1) ||
any(sample.table$Dilution <= 0))
stop("Invalid value for Dilution.")
class(sample.table) <- "sample_table"
return(sample.table)
}
#' Read reference files
#'
#' This function reads the results files of reference samples listed in the
#' sample table. Fluoresce intensity and quality value (just for Thermo Fisher)
#' are collected.
#' If a \code{\link{reference_dbscan}} template file with the same input
#' paramters (reference ID, eps, minPts) is available, fluorescence data,
#' quality value and dbscan analysis results are retrived from the template
#' file.
#' @param sample.table object of class \code{sample_table}, inherited from
#' \code{\link{read_sampleTable}}.
#' @param eps,minPts numeric. Input parameters for the DBSCAN algorithm. If
#' they match the paramters of \code{\link{reference_dbscan}} template file,
#' the data are retrived from the template.
#' @inheritParams dPCP
#' @return An object of class \code{read_reference} containing a sublist for
#' each reference. Each sublist has the following components:
#' \item{quality}{value of the \code{reference.quality} parameter.}
#' \item{data}{a matrix with the fluorescence intensities and quality
#' values.}
#' \item{dbscan}{an object of class \code{dbscan_fast}, inherited from
#' \code{\link[dbscan]{dbscan}}. This component is available only if a
#' \code{\link{reference_dbscan}} template file is used to retrive the
#' data.}
#' @examples
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' #Read sample table file
#' sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
#' file.location = fileLoc)
#'
#' #Read reference files
#' ref <- read_reference(sample.table, system = "bio-rad",
#' file.location = fileLoc)
#' @export
read_reference <- function(sample.table, system = NULL, file.location = ".",
reference.quality = 0.5, eps = NULL,
minPts = NULL) {
if (!inherits(sample.table, "sample_table"))
stop("'sample.table' must be an object of class sample_table")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
reference.quality <- "Defined by Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
system <- "Other"
reference.quality <- "Defined by the supplier"
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if ((system == "Thermo Fisher") & (
!is.numeric(reference.quality) || any(reference.quality > 1) ||
any(reference.quality < 0)))
stop("Invalid value for 'reference.quality'. It must be between 0 and 1")
if ((system == "Thermo Fisher") & (
length(reference.quality) > 1 &
length(reference.quality) != length(unique(sample.table$Reference))))
stop("Invalid value for 'reference.quality'. It must be a numeric value or
a numeric vector of lenght equal to the number of reference samples")
if (!is.character(file.location))
stop("'file.location' must be a path name indicating reference and
sample files location")
if (!is.null(eps) & !is.numeric(eps)) stop("'eps' must be numeric")
if (!is.null(minPts) & !is.numeric(minPts)) stop("'minPts' must be numeric")
if (length(eps) > 1 & length(eps) != length(unique(sample.table$Reference)))
stop("Invalid value for 'eps'. It must be a numeric value or a numeric
vector of lenght equal to the number of reference samples")
if (length(minPts) > 1 & length(minPts) !=
length(unique(sample.table$Reference)))
stop("Invalid value for 'minPts'. It must be a numeric value or a numeric
vector of lenght equal to the number of reference samples")
if (system == "Thermo Fisher") {
#List reference .eds files and DBSCAN reference files (.rts)
reference.filesnames <- sapply(unique(sample.table$Reference), function(x){
eds.files <- list.files(file.location,
pattern = paste0(x, ".eds"))
if (!is.null(eps) & !is.null(minPts)) {
if (length(eps) == 1) {
new.eps <- eps
} else {
new.eps <- eps[match(x, unique(sample.table$Reference))]
}
if (length(minPts) == 1) {
new.minPts <- minPts
} else {
new.minPts <- minPts[match(x, unique(sample.table$Reference))]
}
if (length(reference.quality) == 1) {
DB.files <- list.files(
file.location, pattern = paste0(x, "_", "qlty",
reference.quality, "_",
"eps", new.eps, "_",
"minPts", new.minPts, "_DB",
".rds"))
} else {
DB.files <- list.files(
file.location, pattern = paste0(
x, "_", "qlty",
reference.quality[match(x, unique(sample.table$Reference))],
"_", "eps", new.eps, "_", "minPts", new.minPts, "_DB", ".rds"))
}
} else {
DB.files <- NULL
}
if (length(eds.files) == 0 & length(DB.files) == 0)
stop(paste0("Neither experiment file nor DBSCAN prediction file of
reference", " '", x, "'", " can be found."))
if (length(eds.files) > 1)
stop(paste0("Multiple experiment files for reference", " '", x, "'."))
if (length(DB.files) > 1)
stop(paste0("Multiple DBSCAN prediction files for reference", " '", x,
"'."))
if (length(DB.files) == 1) {
eds.files <- DB.files
}
if (length(eds.files) == 1 & length(DB.files) == 1) {
print(paste0(
"Both experiment and DBSCAN prediction files of reference", " '", x,
"'", " have been found. DBSCAN prediction file will be used for the
analysis."))}
eds.files
})
#Extract data from .eds or .rts files
subquality <- lapply(seq_along(reference.filesnames), function(y) {
#If it is a `.rds` file, extract dbscan results
if (stringr::str_sub(reference.filesnames[y], start = -4) == ".rds") {
quality <- readRDS(paste0(file.location, "/",
reference.filesnames[y]))$quality
data <- readRDS(paste0(file.location, "/",
reference.filesnames[y]))$data
submatrix <- readRDS(paste0(file.location, "/",
reference.filesnames[y]))$dbscan
refdata <- list("quality" = quality, "data" = data,
"dbscan" = submatrix)
} else if (stringr::str_sub(reference.filesnames[y], start = -4) ==
".eds") {
#If it is a `.eds` file, extract fluorescence and quality data
quality.value <- utils::read.csv(
unz(paste0(file.location, "/", reference.filesnames[y]),
"apldbio/sds/quality_metrics/QVhOverallScores.CSV"))
fluorescence <- utils::read.csv(
unz(paste0(file.location, "/", reference.filesnames[y]),
"apldbio/sds/quants_dye/ComponentData.CSV"))
reference.data <- matrix(
c(quality.value[, 1], fluorescence[, 3], fluorescence[, 1]),
ncol = 3, dimnames = list(1:nrow(quality.value),
c("Quality", "Vic", "Fam")))
#Keep data with quality score higher than reference.quality
if (length(reference.quality) == 1) {
submatrix <- subset.matrix(reference.data[, c(2, 3)],
reference.data[, 1] >= reference.quality)
refdata <- list("quality" = reference.quality, "data" = submatrix)
} else {
submatrix <- subset.matrix(
reference.data[, c(2, 3)], reference.data[, 1] >=
reference.quality[y])
refdata <- list("quality" = reference.quality[y], "data" = submatrix)
}
if (nrow(submatrix) < 10000)
stop(paste0("The number of wells qualified by 'reference.quality' is
less than 10000 for reference ", "'",
stringr::str_sub(reference.filesnames[y], start = -10,
end = -5), "'.", "
Try to reduce the quality threshold or run another chip"))
refdata
}
})
} else {
#Extract data from .csv or .rts files
subquality <- lapply(unique(sample.table$Reference), function(y) {
ref.file <- list.files(file.location, pattern = y)
if (length(ref.file) == 0)
stop(paste0("No file of reference", " '", y, "'", " can be found."))
if (length(ref.file) > 1)
stop(paste0("Multiple files for reference", " '", y, "'."))
#If it is a `.rds` file, extract dbscan results
if (stringr::str_sub(ref.file, start = -4) == ".rds") {
quality <- readRDS(paste0(file.location, "/",
ref.file))$quality
data <- readRDS(paste0(file.location, "/",
ref.file))$data
submatrix <- readRDS(paste0(file.location, "/",
ref.file))$dbscan
refdata <- list("quality" = quality, "data" = data,
"dbscan" = submatrix)
} else if (stringr::str_sub(ref.file, start = -4) == ".csv") {
#If it is a `.csv` file, extract fluorescence and quality data
fluorescence <- utils::read.csv(
paste0(file.location, "/", ref.file),
na.strings = c("NA", ""),
colClasses = c("numeric", "numeric"))
data <- matrix(c(fluorescence[,2], fluorescence[,1]), ncol = 2)
colnames(data) <- c("Vic", "Fam")
refdata <- list("quality" = reference.quality, "data" = data)
}
})
}
names(subquality) <- unique(sample.table$Reference)
class(subquality) <- "read_reference"
return(subquality)
}
#' Read sample files
#'
#' This function reads the results files of samples listed in the sample table.
#' Fluoresce intensity and quality value (just for Thermo Fisher) are
#' collected.
#' @inheritParams read_reference
#' @inheritParams dPCP
#' @return An object of class \code{read_sample} containing a sublist for each
#' sample. Each sublist has the following components:
#' \item{quality}{value of the \code{sample.quality} parameter.}
#' \item{data}{a matrix with the fluorescence intensities and quality
#' values.}
#' @examples
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' #Read sample table file
#' sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
#' file.location = fileLoc)
#'
#' #Read reference files
#' ref <- read_reference(sample.table, system = "bio-rad",
#' file.location = fileLoc)
#'
#' #Read samples files
#' samp <- read_sample(sample.table, system = "bio-rad",
#' file.location = fileLoc)
#' @export
read_sample <- function(sample.table, system = NULL, file.location = ".",
sample.quality = 0.5, partition.volume = NULL) {
if (!inherits(sample.table, "sample_table"))
stop("'sample.table' must be an object of class sample_table")
if (!is.character(file.location))
stop("'file.location' must be a path name indicating reference and
sample files location")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
sample.quality <- "Defined by Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
if (is.numeric(partition.volume) & length(partition.volume) == 1) {
system <- "Other"
sample.quality <- paste0(
"Defined by the supplier. Partition volume: ", partition.volume)
} else {
stop("partition.volume must be numeric")
}
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if ((system == "Thermo Fisher") & (
!is.numeric(sample.quality) || any(sample.quality > 1) ||
any(sample.quality < 0)))
stop("Invalid value for 'sample.quality'. It must be between 0 and 1")
if ((system == "Thermo Fisher") & (
length(sample.quality) > 1 &
length(sample.quality) != length(sample.table$Chip.ID.Well.ID)))
stop("Invalid value for 'sample.quality'. It must be a numeric value or
a numeric vector of lenght equal to the number of samples")
#Assign name to the samples (samplename_chipID)
name <- paste(sample.table$Sample.name, sample.table$Chip.ID, sep = "_")
if (system == "Thermo Fisher") {
#List .eds sample files
filesnames <- sapply(sample.table$Chip.ID, function(x) {
eds.files <- list.files(file.location,
pattern = paste0(as.character(x), ".eds"))
if (length(eds.files) == 0)
stop(paste0("Cannot find the file of sample ", x))
if (length(eds.files) > 1)
stop(paste0("Multiple files for sample", x))
eds.files
})
#Extract quality and fluorescence data from .eds files
subquality <- lapply(seq_along(filesnames), function(y) {
quality <- utils::read.csv(
unz(paste0(file.location, "/", filesnames[[y]]),
"apldbio/sds/quality_metrics/QVhOverallScores.CSV"))
fluorescence <- utils::read.csv(
unz(paste0(file.location, "/",filesnames[[y]]),
"apldbio/sds/quants_dye/ComponentData.CSV"))
alldata <- matrix(
c(quality[, 1], fluorescence[, 3], fluorescence[, 1]), ncol = 3,
dimnames = list(1:nrow(quality), c("Quality", "Vic", "Fam")))
#Keep data with quality score higher than reference.quality
if (length(sample.quality) > 1) {
sample.quality <- sample.quality[y]
}
submatrix <- subset.matrix(
alldata[, c(2, 3)], alldata[, 1] >= sample.quality)
submatrix <- list("quality" = sample.quality, "data" = submatrix)
})
} else {
#List .csv sample files
filesnames <- sapply(sample.table$Chip.ID.Well.ID, function(x) {
csv.files <- list.files(
file.location, pattern = paste0(as.character(x), "_Amplitude.csv"))
if (length(csv.files) == 0)
stop(paste0("Cannot find the file of sample ", x))
if (length(csv.files) > 1)
stop(paste0("Multiple files for sample", x))
csv.files
})
subquality <- lapply(filesnames, function(y) {
fluorescence <- utils::read.csv(paste0(file.location, "/", y),
na.strings = c("NA", ""),
colClasses = c("numeric", "numeric"))
data <- matrix(c(fluorescence[,2],fluorescence[,1]), ncol = 2)
colnames(data) <- c("Vic", "Fam")
list("quality" = sample.quality, "data" = data)
})
}
names(subquality) <- name
class(subquality) <- "read_sample"
return(subquality)
}
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Defines functions read_sample read_reference read_sampleTable dbscan_combination
Documented in dbscan_combination read_reference read_sample read_sampleTable
#' Test eps and minPts combinations for DBSCAN analysis
#'
#' This function tests all combinations of eps and minPts for DBSCAN analysis
#' of reference samples indicated in refID. The results are represented in
#' scatterplots exported to a pdf file.
#' @inheritParams dPCP
#' @param refID a string or a character vector of chipID (Thermo Fisher) or
#' the complete file name with the extension (Bio-Rad) of reference sample(s)
#' to be analysed.
#' @param reference.quality numeric. Between 0 and 1. Quality threshold
#' to subset the data (just for Thermo Fisher). If different thresholds have
#' to be applied to various reference samples, a vectror of the same length
#' of \code{refID} has to be provided.
#' @param eps a numeric vector of values to be tested. Maximum distance
#' between elements within a cluster in a DBSCAN analysis.
#' See also \code{\link[dbscan]{dbscan}}.
#' @param minPts a numeric vector of values to be tested. Number of minimum
#' elements to assemble a cluster in a DBSCAN analysis.
#' See also \code{\link[dbscan]{dbscan}}.
#' @return A pdf file containing the scatterplots of DBSCAN analysis performed
#' with all combinations of eps and minPts.
#' Each reference generates a different pdf file.
#' @examples
#' \donttest{
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' dbscan_combination("dilution20200313_B01_Amplitude.csv",
#' file.location = fileLoc, system = "bio-rad",
#' eps = c(150, 160, 180, 190), minPts = c(80, 100, 120))
#'
#' unlink("dilution20200313_B01_Amplitude.pdf")
#' }
#' @export
dbscan_combination <- function(refID, system = NULL, file.location = ".",
reference.quality = 0.5,
eps = c(120, 150, 180, 200),
minPts = c(20, 50, 80, 100)) {
if (!is.character(refID))
stop("'refID' must be a character string or vector")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
reference.quality <- "Defined by Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
system <- "Other"
reference.quality <- "Defined by the supplier"
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if ((system == "Thermo Fisher") & (
!is.numeric(reference.quality) || any(reference.quality > 1) ||
any(reference.quality < 0)))
stop("Invalid value for 'reference.quality'. It must be between 0 and 1")
if ((system == "Thermo Fisher") & (
length(reference.quality) > 1 &
length(reference.quality) != length(unique(refID))))
stop("Invalid value for 'reference.quality'. It must be a numeric value or
a numeric vector of lenght equal to the number of reference samples")
if (!is.numeric(c(eps, minPts))) stop("'eps' and 'minPts' must be numeric")
#Calculate all combinations
combinations <- expand.grid(eps, minPts)
comb <- lapply(seq(length(refID)), function(x) {
if (system == "Thermo Fisher") {
#List reference experiment file
eds.file <- list.files(file.location,
pattern = paste(refID[x], ".eds", sep = ""))
if (length(eds.file) == 0)
stop(paste0("An experiment file of reference", " '", refID[x],
"'", " can not be found."))
if (length(eds.file) > 1)
stop(paste0("Multiple experiment files for reference", " '",
refID[x], "'."))
#Extract fluoresce and quality data
quality.value <- utils::read.csv(
unz(paste0(file.location, "/", eds.file),
"apldbio/sds/quality_metrics/QVhOverallScores.CSV"))
fluorescence <- utils::read.csv(
unz(paste0(file.location, "/", eds.file),
"apldbio/sds/quants_dye/ComponentData.CSV"))
reference.data <- matrix(c(
quality.value[, 1], fluorescence[, 3], fluorescence[, 1]), ncol = 3,
dimnames = list(1:nrow(quality.value), c("Quality", "Vic", "Fam")))
if (length(reference.quality) > 1) {
reference.quality <- reference.quality[x]
}
#Keep data with quality score higher than reference.quality
submatrix <- subset.matrix(
reference.data[, c(2, 3)], reference.data[, 1] >= reference.quality)
if (nrow(submatrix) < 10000)
stop(paste0("The number of wells qualified by reference.quality is less
than 10000 for reference ", "'", refID[x], "'.", "
Try to reduce the quality threshold or run another chip"))
} else {
ref.file <- list.files(file.location, pattern = refID[x])
if (length(ref.file) == 0)
stop(paste0("No file of reference", " '", refID[x], "'",
" can be found."))
if (length(ref.file) > 1)
stop(paste0("Multiple files for reference", " '", refID[x], "'."))
if (stringr::str_sub(ref.file, start = -4) == ".csv") {
#If it is a `.csv` file, extract fluorescence and quality data
fluorescence <- utils::read.csv(
paste0(file.location, "/", ref.file), na.strings = c("NA", ""),
colClasses = c("numeric", "numeric", "NULL"))
submatrix <- matrix(c(fluorescence[,2],fluorescence[,1]), ncol = 2)
colnames(submatrix) <- c("Vic", "Fam")
}
}
#Try all combinations and plot the results
graph.comb <- lapply(seq(nrow(combinations)), function(y) {
dbclus <- dbscan::dbscan(submatrix, combinations[y, 1],
combinations[y, 2])
p <- ggplot(as.data.frame(submatrix), aes_string(x = "Vic", y = "Fam")) +
geom_point(size = 0.5, aes(color = factor(dbclus$cluster))) +
geom_point(size = 0.5,
data = as.data.frame(submatrix)[dbclus$cluster == 0, ],
aes_string(x = "Vic", y = "Fam"), colour = "grey40") +
labs(title = paste0("eps = ", dbclus$eps, ", minPts = ",
dbclus$minPts)) +
theme(
panel.background = element_rect(fill = "white"),
panel.border = element_rect(fill = NA, color = "black"),
legend.position = "none",
plot.title = element_text(size = 14),
axis.title.x = element_text(size = 12),
axis.title.y = element_text(size = 12),
axis.text = element_text(size = 9)
)
})
#Draw 4 plots per page and export to pdf
tot <- ggpubr::ggarrange(plotlist = graph.comb, ncol = 2, nrow = 2)
if (system == "Thermo Fisher") {
ggpubr::ggexport(tot, filename = paste0(refID[x], ".pdf"))
} else {
ggpubr::ggexport(
tot,
filename = paste0(stringr::str_sub(refID[x], end = -5), ".pdf"))
}
})
}
#' Read sample table
#'
#' This function reads a file containing the essential information about the
#' samples and experimental settings. The file has to be filled out by the user
#' and formatted as described in the vignette.
#' @inheritParams dPCP
#' @return An object of class \code{sample_table}.
#' @examples
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' #Read sample table file
#' sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
#' file.location = fileLoc)
#' @export
read_sampleTable <- function(file, system = NULL, file.location = ".") {
if (!is.character(file)) stop("'file' must be a character string")
if (stringr::str_sub(file, start = -4) != ".csv")
stop("'file' must be a '.csv' file. Please use the template provided.")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
system <- "Other"
reference.quality <- "Defined by the supplier"
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if (!is.character(file.location))
stop("'file.location' must be a path name indicating reference and
sample files location")
sample.table <- utils::read.csv(file,
stringsAsFactors = FALSE,
na.strings = c("NA", ""))
if (ncol(sample.table) != 9)
stop("Columns number is not correct. Please use the template provided.")
if (any(colnames(sample.table) !=
c("Sample.name", "Chip.ID.Well.ID", "No.of.targets", "FAM.target",
"Target.3", "Target.4", "VIC.HEX.target", "Reference",
"Dilution")) ||
any(is.na(colnames(sample.table))))
stop("Columns names are not correct. Please use the template provided.")
if (any(grepl(",", sample.table))) {
new.col <- lapply(sample.table[, c(1, 4:7)], function(x) {
x <- gsub(",", ".", x)
})
sample.table[, c(1, 4:7)] <- new.col
}
if (any(is.na(sample.table$Sample.name))) {
na.names <- sapply(which(is.na(sample.table$Sample.name)), function(x) {
paste0("Sample", x)
})
sample.table$Sample.name[which(is.na(sample.table$Sample.name))] <-
na.names
}
if (any(is.na(sample.table$Chip.ID.Well.ID)))
stop("Sample Chip or Well ID must be provided")
if (!is.integer(sample.table$No.of.targets) ||
any(is.na(sample.table$No.of.targets)) ||
any(sample.table$No.of.targets > 4) ||
any(sample.table$No.of.targets < 1))
stop("Invalid value for No of targets")
if (any(duplicated(sample.table$Sample.name)) &&
any(duplicated(sample.table$Sample.name) !=
duplicated(paste(sample.table$Sample.name,
sample.table$No.of.targets,"_"))))
stop("Replicates must have the same number of targets")
if (any(is.na(sample.table$Reference))) {
ref <- lapply(which(is.na(sample.table$Reference)), function(x) {
if (system == "Thermo Fisher") {
ref.file <- sample.table$Chip.ID.Well.ID[x]
} else {
ref.file <- list.files(
file.location,
pattern = paste0(as.character(sample.table$Chip.ID.Well.ID[x]),
"_Amplitude.csv"))
}
if (length(ref.file) > 1) {
stop(paste0("More than one file has been found for the sample ",
sample.table$Chip.ID.Well.ID[x]))
} else if (length(ref.file) == 0)
stop(paste0("No file has been found for the sample ",
sample.table$Chip.ID.Well.ID[x]))
ref.file
})
sample.table$Reference[which(is.na(sample.table$Reference))] <-
unlist(ref)
}
if (!is.numeric(sample.table$Dilution) ||
any(is.na(sample.table$Dilution)) ||
any(sample.table$Dilution > 1) ||
any(sample.table$Dilution <= 0))
stop("Invalid value for Dilution.")
class(sample.table) <- "sample_table"
return(sample.table)
}
#' Read reference files
#'
#' This function reads the results files of reference samples listed in the
#' sample table. Fluoresce intensity and quality value (just for Thermo Fisher)
#' are collected.
#' If a \code{\link{reference_dbscan}} template file with the same input
#' paramters (reference ID, eps, minPts) is available, fluorescence data,
#' quality value and dbscan analysis results are retrived from the template
#' file.
#' @param sample.table object of class \code{sample_table}, inherited from
#' \code{\link{read_sampleTable}}.
#' @param eps,minPts numeric. Input parameters for the DBSCAN algorithm. If
#' they match the paramters of \code{\link{reference_dbscan}} template file,
#' the data are retrived from the template.
#' @inheritParams dPCP
#' @return An object of class \code{read_reference} containing a sublist for
#' each reference. Each sublist has the following components:
#' \item{quality}{value of the \code{reference.quality} parameter.}
#' \item{data}{a matrix with the fluorescence intensities and quality
#' values.}
#' \item{dbscan}{an object of class \code{dbscan_fast}, inherited from
#' \code{\link[dbscan]{dbscan}}. This component is available only if a
#' \code{\link{reference_dbscan}} template file is used to retrive the
#' data.}
#' @examples
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' #Read sample table file
#' sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
#' file.location = fileLoc)
#'
#' #Read reference files
#' ref <- read_reference(sample.table, system = "bio-rad",
#' file.location = fileLoc)
#' @export
read_reference <- function(sample.table, system = NULL, file.location = ".",
reference.quality = 0.5, eps = NULL,
minPts = NULL) {
if (!inherits(sample.table, "sample_table"))
stop("'sample.table' must be an object of class sample_table")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
reference.quality <- "Defined by Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
system <- "Other"
reference.quality <- "Defined by the supplier"
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if ((system == "Thermo Fisher") & (
!is.numeric(reference.quality) || any(reference.quality > 1) ||
any(reference.quality < 0)))
stop("Invalid value for 'reference.quality'. It must be between 0 and 1")
if ((system == "Thermo Fisher") & (
length(reference.quality) > 1 &
length(reference.quality) != length(unique(sample.table$Reference))))
stop("Invalid value for 'reference.quality'. It must be a numeric value or
a numeric vector of lenght equal to the number of reference samples")
if (!is.character(file.location))
stop("'file.location' must be a path name indicating reference and
sample files location")
if (!is.null(eps) & !is.numeric(eps)) stop("'eps' must be numeric")
if (!is.null(minPts) & !is.numeric(minPts)) stop("'minPts' must be numeric")
if (length(eps) > 1 & length(eps) != length(unique(sample.table$Reference)))
stop("Invalid value for 'eps'. It must be a numeric value or a numeric
vector of lenght equal to the number of reference samples")
if (length(minPts) > 1 & length(minPts) !=
length(unique(sample.table$Reference)))
stop("Invalid value for 'minPts'. It must be a numeric value or a numeric
vector of lenght equal to the number of reference samples")
if (system == "Thermo Fisher") {
#List reference .eds files and DBSCAN reference files (.rts)
reference.filesnames <- sapply(unique(sample.table$Reference), function(x){
eds.files <- list.files(file.location,
pattern = paste0(x, ".eds"))
if (!is.null(eps) & !is.null(minPts)) {
if (length(eps) == 1) {
new.eps <- eps
} else {
new.eps <- eps[match(x, unique(sample.table$Reference))]
}
if (length(minPts) == 1) {
new.minPts <- minPts
} else {
new.minPts <- minPts[match(x, unique(sample.table$Reference))]
}
if (length(reference.quality) == 1) {
DB.files <- list.files(
file.location, pattern = paste0(x, "_", "qlty",
reference.quality, "_",
"eps", new.eps, "_",
"minPts", new.minPts, "_DB",
".rds"))
} else {
DB.files <- list.files(
file.location, pattern = paste0(
x, "_", "qlty",
reference.quality[match(x, unique(sample.table$Reference))],
"_", "eps", new.eps, "_", "minPts", new.minPts, "_DB", ".rds"))
}
} else {
DB.files <- NULL
}
if (length(eds.files) == 0 & length(DB.files) == 0)
stop(paste0("Neither experiment file nor DBSCAN prediction file of
reference", " '", x, "'", " can be found."))
if (length(eds.files) > 1)
stop(paste0("Multiple experiment files for reference", " '", x, "'."))
if (length(DB.files) > 1)
stop(paste0("Multiple DBSCAN prediction files for reference", " '", x,
"'."))
if (length(DB.files) == 1) {
eds.files <- DB.files
}
if (length(eds.files) == 1 & length(DB.files) == 1) {
print(paste0(
"Both experiment and DBSCAN prediction files of reference", " '", x,
"'", " have been found. DBSCAN prediction file will be used for the
analysis."))}
eds.files
})
#Extract data from .eds or .rts files
subquality <- lapply(seq_along(reference.filesnames), function(y) {
#If it is a `.rds` file, extract dbscan results
if (stringr::str_sub(reference.filesnames[y], start = -4) == ".rds") {
quality <- readRDS(paste0(file.location, "/",
reference.filesnames[y]))$quality
data <- readRDS(paste0(file.location, "/",
reference.filesnames[y]))$data
submatrix <- readRDS(paste0(file.location, "/",
reference.filesnames[y]))$dbscan
refdata <- list("quality" = quality, "data" = data,
"dbscan" = submatrix)
} else if (stringr::str_sub(reference.filesnames[y], start = -4) ==
".eds") {
#If it is a `.eds` file, extract fluorescence and quality data
quality.value <- utils::read.csv(
unz(paste0(file.location, "/", reference.filesnames[y]),
"apldbio/sds/quality_metrics/QVhOverallScores.CSV"))
fluorescence <- utils::read.csv(
unz(paste0(file.location, "/", reference.filesnames[y]),
"apldbio/sds/quants_dye/ComponentData.CSV"))
reference.data <- matrix(
c(quality.value[, 1], fluorescence[, 3], fluorescence[, 1]),
ncol = 3, dimnames = list(1:nrow(quality.value),
c("Quality", "Vic", "Fam")))
#Keep data with quality score higher than reference.quality
if (length(reference.quality) == 1) {
submatrix <- subset.matrix(reference.data[, c(2, 3)],
reference.data[, 1] >= reference.quality)
refdata <- list("quality" = reference.quality, "data" = submatrix)
} else {
submatrix <- subset.matrix(
reference.data[, c(2, 3)], reference.data[, 1] >=
reference.quality[y])
refdata <- list("quality" = reference.quality[y], "data" = submatrix)
}
if (nrow(submatrix) < 10000)
stop(paste0("The number of wells qualified by 'reference.quality' is
less than 10000 for reference ", "'",
stringr::str_sub(reference.filesnames[y], start = -10,
end = -5), "'.", "
Try to reduce the quality threshold or run another chip"))
refdata
}
})
} else {
#Extract data from .csv or .rts files
subquality <- lapply(unique(sample.table$Reference), function(y) {
ref.file <- list.files(file.location, pattern = y)
if (length(ref.file) == 0)
stop(paste0("No file of reference", " '", y, "'", " can be found."))
if (length(ref.file) > 1)
stop(paste0("Multiple files for reference", " '", y, "'."))
#If it is a `.rds` file, extract dbscan results
if (stringr::str_sub(ref.file, start = -4) == ".rds") {
quality <- readRDS(paste0(file.location, "/",
ref.file))$quality
data <- readRDS(paste0(file.location, "/",
ref.file))$data
submatrix <- readRDS(paste0(file.location, "/",
ref.file))$dbscan
refdata <- list("quality" = quality, "data" = data,
"dbscan" = submatrix)
} else if (stringr::str_sub(ref.file, start = -4) == ".csv") {
#If it is a `.csv` file, extract fluorescence and quality data
fluorescence <- utils::read.csv(
paste0(file.location, "/", ref.file),
na.strings = c("NA", ""),
colClasses = c("numeric", "numeric"))
data <- matrix(c(fluorescence[,2], fluorescence[,1]), ncol = 2)
colnames(data) <- c("Vic", "Fam")
refdata <- list("quality" = reference.quality, "data" = data)
}
})
}
names(subquality) <- unique(sample.table$Reference)
class(subquality) <- "read_reference"
return(subquality)
}
#' Read sample files
#'
#' This function reads the results files of samples listed in the sample table.
#' Fluoresce intensity and quality value (just for Thermo Fisher) are
#' collected.
#' @inheritParams read_reference
#' @inheritParams dPCP
#' @return An object of class \code{read_sample} containing a sublist for each
#' sample. Each sublist has the following components:
#' \item{quality}{value of the \code{sample.quality} parameter.}
#' \item{data}{a matrix with the fluorescence intensities and quality
#' values.}
#' @examples
#' library(dPCP)
#'
#' #Find path of sample table and location of reference and input files
#' sampleTable <- system.file("extdata", "Template_sampleTable.csv",
#' package = "dPCP")
#'
#' fileLoc <- system.file("extdata", package = "dPCP")
#'
#' #Read sample table file
#' sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
#' file.location = fileLoc)
#'
#' #Read reference files
#' ref <- read_reference(sample.table, system = "bio-rad",
#' file.location = fileLoc)
#'
#' #Read samples files
#' samp <- read_sample(sample.table, system = "bio-rad",
#' file.location = fileLoc)
#' @export
read_sample <- function(sample.table, system = NULL, file.location = ".",
sample.quality = 0.5, partition.volume = NULL) {
if (!inherits(sample.table, "sample_table"))
stop("'sample.table' must be an object of class sample_table")
if (!is.character(file.location))
stop("'file.location' must be a path name indicating reference and
sample files location")
if (any(c("Thermo Fisher", "ThermoFisher", "thermo fisher", "thermofisher",
"Thermo", "thermo", "t", "T") == system)) {
system <- "Thermo Fisher"
} else if (any(c("Bio-Rad", "BioRad", "Bio-rad", "Biorad", "bio-rad",
"biorad", "Bio", "bio", "B", "b") == system)) {
system <- "Bio-Rad"
sample.quality <- "Defined by Bio-Rad"
} else if (any(c("Other", "other", "O", "o") == system)) {
if (is.numeric(partition.volume) & length(partition.volume) == 1) {
system <- "Other"
sample.quality <- paste0(
"Defined by the supplier. Partition volume: ", partition.volume)
} else {
stop("partition.volume must be numeric")
}
} else {stop("system must be either Thermo Fisher, Bio-Rad, or other")}
if ((system == "Thermo Fisher") & (
!is.numeric(sample.quality) || any(sample.quality > 1) ||
any(sample.quality < 0)))
stop("Invalid value for 'sample.quality'. It must be between 0 and 1")
if ((system == "Thermo Fisher") & (
length(sample.quality) > 1 &
length(sample.quality) != length(sample.table$Chip.ID.Well.ID)))
stop("Invalid value for 'sample.quality'. It must be a numeric value or
a numeric vector of lenght equal to the number of samples")
#Assign name to the samples (samplename_chipID)
name <- paste(sample.table$Sample.name, sample.table$Chip.ID, sep = "_")
if (system == "Thermo Fisher") {
#List .eds sample files
filesnames <- sapply(sample.table$Chip.ID, function(x) {
eds.files <- list.files(file.location,
pattern = paste0(as.character(x), ".eds"))
if (length(eds.files) == 0)
stop(paste0("Cannot find the file of sample ", x))
if (length(eds.files) > 1)
stop(paste0("Multiple files for sample", x))
eds.files
})
#Extract quality and fluorescence data from .eds files
subquality <- lapply(seq_along(filesnames), function(y) {
quality <- utils::read.csv(
unz(paste0(file.location, "/", filesnames[[y]]),
"apldbio/sds/quality_metrics/QVhOverallScores.CSV"))
fluorescence <- utils::read.csv(
unz(paste0(file.location, "/",filesnames[[y]]),
"apldbio/sds/quants_dye/ComponentData.CSV"))
alldata <- matrix(
c(quality[, 1], fluorescence[, 3], fluorescence[, 1]), ncol = 3,
dimnames = list(1:nrow(quality), c("Quality", "Vic", "Fam")))
#Keep data with quality score higher than reference.quality
if (length(sample.quality) > 1) {
sample.quality <- sample.quality[y]
}
submatrix <- subset.matrix(
alldata[, c(2, 3)], alldata[, 1] >= sample.quality)
submatrix <- list("quality" = sample.quality, "data" = submatrix)
})
} else {
#List .csv sample files
filesnames <- sapply(sample.table$Chip.ID.Well.ID, function(x) {
csv.files <- list.files(
file.location, pattern = paste0(as.character(x), "_Amplitude.csv"))
if (length(csv.files) == 0)
stop(paste0("Cannot find the file of sample ", x))
if (length(csv.files) > 1)
stop(paste0("Multiple files for sample", x))
csv.files
})
subquality <- lapply(filesnames, function(y) {
fluorescence <- utils::read.csv(paste0(file.location, "/", y),
na.strings = c("NA", ""),
colClasses = c("numeric", "numeric"))
data <- matrix(c(fluorescence[,2],fluorescence[,1]), ncol = 2)
colnames(data) <- c("Vic", "Fam")
list("quality" = sample.quality, "data" = data)
})
}
names(subquality) <- name
class(subquality) <- "read_sample"
return(subquality)
}
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