ImportSamples | R Documentation |
These functions import sample information from either a tab delimited file or a file system path. The sample information contain sample names, CDF files and their measurement day, also known as, measurement run or measurement batch.
ImportSamples(sampfile, CDFpath, RIpath, ftype=c("binary", "text"), ...)
ImportSamplesFromDir(CDFpath=".", RIfiles=FALSE, ftype=c("binary", "text"),
verbose=FALSE, ...)
sampfile |
A character string naming a sample file or a |
CDFpath |
A character string naming a directory where the CDF files are located (by default is the current directory) |
RIpath |
A character string naming a directory where the RI corrected text files are/will be located. |
RIfiles |
Logical. If |
ftype |
A character string giving the file type for RI files. Options are "binary" and "text". |
verbose |
Logical. Show more output if |
... |
Extra options whose meaning depend on the function: for |
.
The sample file is a tab-delimited text file or, alternatively, a
data.frame
like the one would get by calling
read.delim
. The following columns
are expected, though only the first one below is mandatory.
CDF_FILE
- The list of baseline corrected CDF files (mandatory).
MEASUREMENT_DAY
- The day or batch when the sample was measured (optional).
SAMPLE_NAME
- A unique sample identifier (optional).
The function first looks for columns matching those names. If they are not found, then it looks for columns with the substrings 'cdf', 'day' and 'name' respectively. If the 'cdf' column is not found, the function raises an error, but if 'day' is not found, then it assumes the measurement day is the same for all. Moreover, if the column for sample names/identifiers is missing, then the function uses the 'cdf' file names as identifiers.
During the column matching, the first match is taken in case of ambiguity. The column order does not matter. Other columns could be included in that file. They won't be used by the script, but will be included in the "sample" R object.
The files given in the 'cdf' column may optionally include a relative path,
such as mypath/myfile.cdf
, which will be relative to the working
directory or relative to the argument CDFpath
. Optionally, the
file extension can be omitted because ‘TargetSearch’ adds the .cdf
extension automatically if missing. Note: it may fail in case sensitive
file systems as a lower case extension is appended.
If the parameter CDFpath
is missing, then the current directory
is used. If RIpath
is missing, the value of CDFpath
will
be used.
The ftype
parameter sets the file format of the RI files, which
are created by the function RIcorrect
. "text" is the
classic text format and "binary" is a binary version, designed
for speed, of the text format (TargetSearch >= 1.12.0). The file format
can be identified by the file extension (".txt" for text, ".dat" for
binary), but this is just an indicator: the file format is detected
dynamically during file reading. Use the method fileFormat
to set or get this parameter.
The function ImportSamplesFromDir
scans for cdf files in the current
or given directory. The search can be made recursive by passing the
parameter recursive=TRUE
(actually passed to dir
).
The parameter verbose
will print a list of detected files
is set to TRUE
. This can be used for debugging.
A tsSample
object.
Alvaro Cuadros-Inostroza, Matthew Hannah, Henning Redestig
ImportLibrary
, tsSample
# get the sample definition definition file
require(TargetSearchData)
cdfpath <- tsd_data_path()
sample.file <- tsd_file_path("samples.txt")
# set a path where the RI files will be created
RIpath <- "."
# import samples
sampleDescription <- ImportSamples(sample.file, CDFpath = cdfpath, RIpath = RIpath)
# change the sample names. It is required that the names must be unique.
sampleNames(sampleDescription) <- paste("Sample", 1:length(sampleDescription), sep = "_")
# change the file paths (relative to the working path)
CDFpath(sampleDescription) <- "my_cdfs"
RIpath(sampleDescription) <- "my_RIs"
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