readOmics: Read in omics data.
In pwOmics: Pathway-based data integration of omics data

Description Usage Arguments Value Examples

This function reads omics data: differentially expressed genes and relatively differentially abundant proteins with corresponding fold changes for each time point.

1	readOmics(tp_prots, tp_genes, omics, PWdatabase, TFtargetdatabase)

`tp_prots`	numeric vector of protein timepoints used in experiment; in case of single time point experiments simply assign an experiment number (e.g. 1).
`tp_genes`	numeric vector of gene/transcript timepoints used in experiment; in case of single time point experiments simply assign an experiment number (e.g. 1).
`omics`	list containing protein and gene IDs and fold changes: Input are two lists, one for protein data, one for gene data, both including a vector of all measured IDs as first element and a list as second element including for each tp a dataframe with IDs and foldchanges per timepoint.
`PWdatabase`	character vector of pathway database names which should be used for pathway identification, possible choices are "biocarta", "kegg", "nci", "reactome".
`TFtargetdatabase`	character vector of TF target database names which should be used for transcription factor/target gene identification, possible choices are "chea", "pazar", "userspec". In case the user is able to provide an own list of transcription factor target gene matches, he can indicate this via "userspec".

OmicsData object: list of 4 elements (OmicsD, PathwayD, TFtargetsD, Status); OmicsD containing omics data set + results (after analysis); PathwayD containing selected pathway databases + biopax model; TFtargetsD containing selected TF target gene databases + TF target gene data.

## Not run: 
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"))

## End(Not run)