tpptrImport imports several tables of protein fold
changes and stores them in a list of ExpressionSets for use in the
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either a dataframe or the path to a spreadsheet. In both cases it specifies necessary information of the TPP-CCR experiment.
single dataframe, or list of dataframes, containing fold change
measurements and additional annotation columns to be imported. Can be used
instead of specifying the file path in
character string indicating which data column provides the unique identifiers for each protein.
character string indicating which columns contain the actual
fold change values. Those column names containing the suffix
character vector indicating missing values in the data table.
When reading data from file, this value will be passed on to the argument
character string indicating which column can be used for additional quality criteria when deciding between different non-unique protein identifiers.
output format. Either "eSetList" to obtain output in the same way as previously (will be deprecated soon), or "tidy" to obtain a
The imported datasets have to contain measurements obtained by TPP-TR experiments. Fold changes need to be pre-computed using the lowest temperature as reference.
An arbitrary number of datasets can be specified by filename in the
Path-column of the
configTable argument, or given directly as
a list of dataframes in the
data argument. They can differ, for
example, by biological replicate or by experimental condition (for example,
treatment versus vehicle). Their names are defined uniquely by the
Experiment column in
configTable. Experimental conditions can
be specified by an optional column in
The default settings are adjusted to analyze data of the python package
isobarQuant. You can also customize them for your own dataset.
configTable argument is a dataframe, or the path to a
spreadsheet (tab-delimited text-file without quoted strings, or xlsx format).
Information about each experiment is stored row-wise.
It contains the following columns:
Path:location of each datafile. Alternatively,
data can be directly handed over by the
Experiment: unique experiment names.
Condition: experimental conditions of each dataset.
Label columns: each isobaric label names a column that contains the temperatures administered for the label in the individual experiments.
Proteins with NAs in the data column specified by
unique generic IDs so that they can be processed by the package.
A list of ExpressionSets storing the imported data for experiment.
Each ExpressionSet contains the measured fold changes, as well as row and
column metadata. In each ExpressionSet
S, the fold changes can be
exprs(S). Protein expNames can be accessed by
featureNames(S). Isobaric labels and the corresponding temperatures are
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