temp_correlations: Plot temporal correlations of phosphoprotein expression...

Description Usage Arguments Value Examples

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

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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

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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)

MarenS2/pwOmics_maren documentation built on May 6, 2019, 3:27 p.m.