tpp2dNormalize: Median normalization of protein fold changes of 2D-TPP data

In TPP: Analyze thermal proteome profiling (TPP) experiments

Description

Normalizes fold changes retrieved from 2D-TPP experiment by dividing by the median fold change

Usage

tpp2dNormalize(configTable = NULL, data, fcStr = NULL)

Arguments

configTable	DEPRECATED
data	data frame that contains the data for the 2D-TPP experiment
fcStr	DEPRECATED

Value

A dataframe identical to the input dataframe except that the columns containing the fold change values have been normalized by their median.

Examples

# Preparation:
data(panobinostat_2DTPP_smallExample)

# Import data:
datIn <- tpp2dImport(configTable = panobinostat_2DTPP_config,
                      data = panobinostat_2DTPP_data,
                      idVar = "representative",
                      addCol = "clustername",
                      intensityStr = "sumionarea_protein_",
                      nonZeroCols = "qusm")

# Compute fold changes:
datFC <- tpp2dComputeFoldChanges(data = datIn)

# Perform median normalization:
datNorm <- tpp2dNormalize(data = datFC)

# View updated attributes. Now contain field 'fcStrNorm' indicating prefix
# of the fold change columns after normalization.
attr(datNorm, "importSettings")["fcStrNorm"]
  

Example output

Loading required package: dplyr

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Loading required package: magrittr
Loading required package: tidyr

Attaching package: 'tidyr'

The following object is masked from 'package:magrittr':

    extract

Removing empty 'Path' column from config table
The following valid label columns were detected:
126, 127L, 127H, 128L, 128H, 129L, 129H, 130L, 130H, 131L.
Importing data...
Importing 2D-TPP dataset: X020466
Removing duplicate identifiers using quality column 'qupm'...
484 out of 484 rows kept for further analysis.
Importing 2D-TPP dataset: X020466
Removing duplicate identifiers using quality column 'qupm'...
484 out of 484 rows kept for further analysis.
Importing 2D-TPP dataset: X020467
Removing duplicate identifiers using quality column 'qupm'...
478 out of 478 rows kept for further analysis.
Importing 2D-TPP dataset: X020467
Removing duplicate identifiers using quality column 'qupm'...
478 out of 478 rows kept for further analysis.
Importing 2D-TPP dataset: X020468
Removing duplicate identifiers using quality column 'qupm'...
448 out of 448 rows kept for further analysis.
Importing 2D-TPP dataset: X020468
Removing duplicate identifiers using quality column 'qupm'...
448 out of 448 rows kept for further analysis.
Importing 2D-TPP dataset: X020469
Removing duplicate identifiers using quality column 'qupm'...
372 out of 372 rows kept for further analysis.
Importing 2D-TPP dataset: X020469
Removing duplicate identifiers using quality column 'qupm'...
372 out of 372 rows kept for further analysis.
Importing 2D-TPP dataset: X020470
Removing duplicate identifiers using quality column 'qupm'...
306 out of 306 rows kept for further analysis.
Importing 2D-TPP dataset: X020470
Removing duplicate identifiers using quality column 'qupm'...
306 out of 306 rows kept for further analysis.
Importing 2D-TPP dataset: X020471
Removing duplicate identifiers using quality column 'qupm'...
261 out of 261 rows kept for further analysis.
Importing 2D-TPP dataset: X020471
Removing duplicate identifiers using quality column 'qupm'...
261 out of 261 rows kept for further analysis.
Reformating data for input into function 'analyzeTPPCCR' ...
Done.
There were 50 or more warnings (use warnings() to see the first 50)
Looking for intensity column prefix: 'sumionarea_protein_'
Computing fold changes...
Done.
Found the following column name in attr(data, 'importSettings')$proteinIdCol: 'representative'
Found the following column name in attr(data, 'importSettings')$fcStr: 'rel_fc_'
Performing median normalization per temperature...
Done.
$fcStrNorm
[1] "norm_rel_fc_"

TPP documentation built on Nov. 8, 2020, 5:55 p.m.