exportTable {twoddpcr} | R Documentation

## Exports an object to file.

### Description

If given a data frame, `exportTable` exports the whole data frame to file. This could be a data frame of any form. A few options are available that can be used to determine the format of the file that is exported, e.g. using a heading for the row names 'column', or omitting row names altogether.

If a `ddpcrWell` is given, `exportTable` exports to a single file with specified/all classification methods.

If a `ddpcrPlate` is given, `exportTable` exports to a directory in the given `location`, where one file is created for each of the wells. If it does not exist, the directory `location` will be created as long as all other parent directories exist.

`exportZip` takes a `ddpcrPlate` object and exports it as a zip file.

### Usage

    exportTable(theObject, location, delim = ",", ...)

    ## S4 method for signature 'data.frame'
    exportTable(
      theObject,
      location,
      delim = ",",
      leadingColName = NULL,
      row.names = TRUE
    )

    ## S4 method for signature 'ddpcrWell'
    exportTable(theObject, location, delim = ",", cMethod = NULL)

    ## S4 method for signature 'ddpcrPlate'
    exportTable(
      theObject,
      location,
      delim = ",",
      cMethod = NULL,
      prefix = "",
      suffix = "_Amplitude.csv"
    )

    exportZip(
      theObject,
      location,
      delim = ",",
      cMethod = NULL,
      prefix = "",
      suffix = "_Amplitude.csv"
    )

    ## S4 method for signature 'ddpcrPlate'
    exportZip(
      theObject,
      location,
      delim = ",",
      cMethod = NULL,
      prefix = "",
      suffix = "_Amplitude.csv"
    )

### Arguments

`theObject` | The dataframe to export.
`location` | The location to export to. This should be a filename if we are using `exportZip`, or we are using `exportTable` and `theObject` is a data frame or `ddpcrWell` object. If `theObject` is a `ddpcrPlate` object, this should be a directory.
`delim` | The character to use as a field separator. Defaults to ",", i.e. export a CSV.
`...` | Other options depending on the type of `theObject`.
`leadingColName` | The name of the leading column, i.e. the 'row names' of the dataframe. This could be a patient identifier or the well used in the ddPCR experiment. If `NULL`, the exported heading will be an empty string. Defaults to `NULL`.
`row.names` | If `NULL`, exports a column corresponding to the row names; if `FALSE`, no such column is included. If 'leadingColName' is not `FALSE`, row.names is assumed to be `FALSE`. Defaults to `TRUE`.
`cMethod` | The name or column number of the classification methods in a `ddpcrWell` or `ddpcrPlate` object to export to file. If `NULL`, all of the classification methods are exported. Defaults to `NULL`.
`prefix` | For `ddpcrPlate` objects, this is the prefix to prepend to the output filenames.
`suffix` | For `ddpcrPlate` objects, this is the suffix to append to the output filenames. This is typically the filename extension, e.g. ".csv" or ".txt". Defaults to ".csv".

### Details

Note that filenames of the form `Anything_A01_Amplitude.csv` can be read by `readCSVDataFrame` so that the well name can be extracted successfully (in this case `A01`). Where it is used, see the default value of the parameter `suffix`.

### Value

Exports a file.

### Author(s)

Anthony Chiu, anthony.chiu@cruk.manchester.ac.uk

### Examples

    ## Output to a temporary directory.
    tmpOut <- file.path(normalizePath(tempdir()))

    ## Read some counts data and generate a summary data frame.
    df <- fullCountsSummary(KRAScountsQS)
    summaryDf <- fullCopiesSummary(df)

    ## Write the summary to a CSV file.
    exportTable(summaryDf, file.path(tmpOut, "summary-table.csv"))

    ## Write the summary to a tab-separated text file.
    exportTable(summaryDf, file.path(tmpOut, "summary-table.txt"), delim="\t")

    ## Write the summary to a CSV file with leading column labelled "Patient".
    exportTable(summaryDf, file.path(tmpOut, "summary-table.csv"),
                leadingColName="Patient")

    ## Read a droplet amplitude CSV file to a ddpcrWell object.
    ampFile <- system.file("extdata", "amplitudes", "sample_B03_Amplitude.csv",
                           package="twoddpcr")
    aWell <- ddpcrWell(well=ampFile)

    ## Classify the droplets into 4 clusters.
    aWell <- kmeansClassify(aWell, centres=4)

    ## Write the amplitudes to a CSV file with the old and new classifications.
    exportTable(aWell,
      location=file.path(tmpOut, "With_Kmeans_B03_Amplitude.csv"))

    ## Write the amplitudes to a CSV file with the new classification only.
    exportTable(aWell,
      location=file.path(tmpOut, "With_Kmeans_B03_Amplitude.csv"),
      cMethod="kmeans")

    ## Read all amplitude files in a directory to a ddpcrPlate object.
    moreAmpsDir <- system.file("extdata", "more-amplitudes", package="twoddpcr")
    krasPlate <- ddpcrPlate(wells=moreAmpsDir)

    ## Classify the droplets into 4 clusters.
    krasPlate <- kmeansClassify(krasPlate, centres=4)

    ## Write the amplitudes to multiple files in a directory with the old and
    ## new classifications.
    exportTable(krasPlate, location=file.path(tmpOut, "amplitudes-classified"))

    ## Write the amplitudes to multiple files with the new classification only
    ## and a custom prefix for the filenames.
    exportTable(krasPlate, location=file.path(tmpOut, "amplitudes-classified"),
                cMethod="kmeans", prefix="Kmeans_Only_")

    ## Export to a zip file.
    exportZip(krasPlate,
              location=file.path(tmpOut, "amplitudes-classified/all.zip"),
              cMethod="kmeans", prefix="Kmeans_Only_")

[Package twoddpcr version 1.18.0 Index]