temp_correlations {pwOmics} | R Documentation

## Plot temporal correlations of phosphoprotein expression levels and affected downstream transcripts.

### 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)

[Package pwOmics version 1.18.0 Index]