readCSVDataFrame: Read all given CSV files into a list.

In CRUKMI-ComputationalBiology/twoddpcr: Classify 2-d Droplet Digital PCR (ddPCR) data and quantify the number of starting molecules

Description

Bio-Rad's QuantaSoft can export droplet amplitude data from multiple wells into CSV files for each well. This function can read these CSV files into a list. Note that empty wells will be ignored.

Usage

readCSVDataFrame(path, wellCol = FALSE, sortByLetter = FALSE)

Arguments

path	The path containing the CSV files (can be a combination of directories and individual CSV file paths). Each file will have a Ch1.Amplitude, Ch2.Amplitude and possibly classification columns, e.g. by default, QuantaSoft returns a Cluster column too.
wellCol	If TRUE, an additional column is added with the well name. This is useful if we need to merge all the data in the output list and we want to identify the original well of each droplet. Defaults to FALSE.
sortByLetter	If TRUE, the resulting list is sorted by the letter in the well names first, e.g. "A02" comes before "B01". If FALSE, the result is sorted by the numeric component of the well names first, e.g. "B01" comes before "A02". Defaults to FALSE.

Value

A list of data frames, each containing the data from a CSV file with the corresponding well name.

Author(s)

Anthony Chiu, [e-mail]

Examples

## Read all of the droplet amplitudes from CSV files in a directory.
moreAmpsDir <- system.file("extdata", "more-amplitudes", package="twoddpcr")
someWells <- readCSVDataFrame(moreAmpsDir)

## We can read files from directories and files at the same time.
ampFile <- system.file("extdata", "amplitudes", "sample_B03_Amplitude.csv",
                       package="twoddpcr")
someWells <- readCSVDataFrame(c(moreAmpsDir, ampFile))

## If samples have been ordered by "A01", "A02", "A03", etc. instead of
## "A01", "B01", "C01", etc., we can set the sortByLetter flag to TRUE.
someWells <- readCSVDataFrame(moreAmpsDir, sortByLetter=TRUE)

## Setting wellCol to TRUE adds an extra column with the well name. If we
## bind the data frames together, we can track where the droplets came from.
someWells <- readCSVDataFrame(moreAmpsDir, wellCol=TRUE)
someWells <- do.call(rbind, someWells)
head(someWells)
tail(someWells)

CRUKMI-ComputationalBiology/twoddpcr documentation built on Feb. 14, 2021, 9:18 p.m.