tpptrImport {TPP} | R Documentation

## Import TPP-TR datasets for analysis by the `TPP` package.

### Description

`tpptrImport` imports several tables of protein fold changes and stores them in a list of ExpressionSets for use in the `TPP` package.

### Usage

    tpptrImport(configTable, data = NULL, idVar = "gene_name",
      fcStr = "rel_fc_", naStrs = c("NA", "n/d", "NaN"),
      qualColName = "qupm", outputFormat = "eSetList")

### Arguments

`configTable` | either a dataframe or the path to a spreadsheet. In both cases it specifies necessary information of the TPP-CCR experiment.
`data` | 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 `configTable`.
`idVar` | character string indicating which data column provides the unique identifiers for each protein.
`fcStr` | character string indicating which columns contain the actual fold change values. Those column names containing the suffix `fcStr` will be regarded as containing fold change values.
`naStrs` | character vector indicating missing values in the data table. When reading data from file, this value will be passed on to the argument `na.strings` in function `read.delim`.
`qualColName` | character string indicating which column can be used for additional quality criteria when deciding between different non-unique protein identifiers.
`outputFormat` | output format. Either "eSetList" to obtain output in the same way as previously (will be deprecated soon), or "tidy" to obtain a

### Details

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 `configTable`.

The default settings are adjusted to analyze data of the python package `isobarQuant`. You can also customize them for your own dataset.

The `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 `data` argument.

- `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 `idVar` receive unique generic IDs so that they can be processed by the package.

### Value

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 accessed by `Biobase::exprs(S)`. Protein expNames can be accessed by `featureNames(S)`. Isobaric labels and the corresponding temperatures are returned by `S$label` and `S$temperature`

### See Also

`tppccrImport`

### Examples

    data(hdacTR_smallExample)
    tpptrData <- tpptrImport(hdacTR_config, hdacTR_data)

[Package TPP version 3.15.3 Index]