tpptrImport: Import TPP-TR datasets for analysis by the 'TPP' package.

In DoroChilds/TPP: Analyze thermal proteome profiling (TPP) experiments

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)
  

DoroChilds/TPP documentation built on Oct. 31, 2021, 4:38 a.m.