temp_correlations: Plot temporal correlations of phosphoprotein expression...

In pwOmics: Pathway-based data integration of omics data

Description

This function plots an overview of consensus phosphoprotein expression level correlations with those transcripts that are affected downstream in a newly generated folder in the working directory. The following additional information needs to be provided: Phosphorylation information amino acid, position and multiplicity with the expression levels for each of the time points the correlations should be plotted for. Furthermore data tables for fold changes/ratios of phosphoproteins and transcripts that are part of the data_omics object.

Usage

temp_correlations(ConsensusGraph, timepointsprot, timepointstrans,
  foldername = "ProtCons_", trans_sign = "signif_single.csv",
  trans_sign_names, phospho_sign = "mat_phospho.csv", phospho_sign_names)

Arguments

ConsensusGraph	result from static analysis: consensus graph generated by staticConsensusNet function.
timepointsprot	numeric vector with measurement time points in phosphoproteome data set, which should be used for correlation plots
timepointstrans	numeric vector with measurement time points in transcriptome data set, which should be used for correlation plots
foldername	character vector specifying the name of the folder that will be generated for the temporal correlations
trans_sign	character vector specifying a tab-delimited file with the transcriptome expression levels for all time points in timepointstrans
trans_sign_names	character vector specifying column names in the transcriptome file corresponding to the expression levels at different time points.
phospho_sign	character vector specifying a tab-delimited file with the phosphoproteome information (columns 'Gene.names', 'Amino.acid', 'Position', 'Multiplicity') and expression levels for all time points in timepointstrans
phospho_sign_names	character vector specifying column names in the phosphoproteome file corresponding to the expression levels at different time points.
...	further plotting/legend parameters.

Value

pdf file in current working directory.

Examples

data(OmicsExampleData)
data_omics = readOmics(tp_prots = c(0.25, 1, 4, 8, 13, 18, 24), 
tp_genes = c(1, 4, 8, 13, 18, 24), OmicsExampleData,
PWdatabase = c("biocarta", "kegg", "nci", "reactome"), 
TFtargetdatabase = c("userspec"))
data_omics = readPhosphodata(data_omics, 
phosphoreg = system.file("extdata", "phospho_reg_table.txt", 
package = "pwOmics")) 
data_omics = readTFdata(data_omics, 
TF_target_path = system.file("extdata", "TF_targets.txt", 
package = "pwOmics"))
data_omics_plus = readPWdata(data_omics,  
loadgenelists = system.file("extdata/Genelists", package = "pwOmics")) 
## Not run: 
data_omics_plus = identifyPR(data_omics_plus)
setwd(system.file("extdata/Genelists", package = "pwOmics"))
data_omics = identifyPWs(data_omics_plus)
data_omics = identifyTFs(data_omics)
data_omics = identifyRsofTFs(data_omics, 
noTFs_inPW = 1, order_neighbors = 10)
data_omics = identifyPWTFTGs(data_omics)
statConsNet = staticConsensusNet(data_omics)
temp_correlations(statConsNet, timepointsprot = c(1,4,8,13,18,24),
timepointstrans = c(1,4,8,13,18,24), foldername = "ProtCons_", 
trans_sign = system.file("extdata", "signif_single.csv", package = "pwOmics") 
trans_sign_names = c("FC_1",  "FC_2", "FC_3", "FC_4"), 
phospho_sign = system.file("extdata", "mat_phospho.csv", package = "pwOmics") 
phospho_sign_names = c("Rat1", "Rat2", "Rat3", "Rat4")) )

## End(Not run)

pwOmics documentation built on Nov. 8, 2020, 4:55 p.m.