SLAPE.pathvis: Generatig a heatmap of the alteration matrix of a...
In saezlab/SLAPenrich: Sample-population Level Analysis of Pathway enrichments

Description Usage Arguments Note Author(s) See Also Examples

This function generates a pdf file containing a heatmap of the alteration matrix of a SLAPenriched pathway across the samples of the analysed dataset, after permuting rows and columns to highlight trend of mutual exclusivity in the alteration-patterns.

Additionally, it generates, a pdf file with three barplots indicating, respectively: (i) the number of mutated genes across samples; (ii) the probabilities of the pathway under consideration to be altered across samples, together with the expected number of samples with alteration in the pathway under consideration; (iii) The observed pathway alteration status across samples, together with the observed total number of samples with alteration in the pathway under consideration.

1	SLAPE.pathvis(EM, PFP, Id, prefName = NULL, PATH = "./", PATH_COLLECTION)

`EM`	A sparse binary matrix, or a sparse matrix with integer non-null entries. In this matrix the column names are sample identifiers, and the row names official HUGO gene symbols. A non-zero entry in position i,j of this matrix indicates the presence of a somatic mutations harbored by the j-sample in the i-gene. This matrix must be the same that has been inputted to the `SLAPE.analyse` function to produce the results in the `PFP` list.
`PFP`	A list containing the SLAPenrich analysis results outputted by the `SLAPE.analyse` function while analysing the genomic dataset summarised by the `EM` genomic event matrix.
`Id`	The index of the pathway for which the pdf files should be produced in the vectors/lists of the pathway collection set specified in `PATH_COLLECTION`.
`prefName`	A string specifing the prefix to be added to the pdf file name (NULL by default).
`PATH`	String specifiying the path of the pdf file to be created (including its name).
`PATH_COLLECTION`	The pathway collection that has been tested against the `EM` dataset with the `SLAPE.analyse` function to produce the `PFP` list of results.

This function makes use of the SLAPE.heuristic_mut_ex_sorting function to realise the mutual exclusivity sorting of the pathway alteration matrix, and it is iteratively used by SLAPE.serialPathVis to generate pdf files with heatmaps and barplots for all the SLAPenriched pathways found in a list of results generated by SLAPE.analyse.

Francesco Iorio - iorio@ebi.ac.uk

SLAPE.analyse, SLAPE.serialPathVis

    #Loading the Genomic Event data object derived from variants annotations
    #identified in 188 Lung Adenocarcinoma patients (Ding et al, 2008)
    data(LUAD_CaseStudy_ugs)

    #Loading KEGG pathway gene-set collection data object
    data(SLAPE.MSigDB_KEGG_hugoUpdated)

    #Loading genome-wide total exonic block lengths
    data(SLAPE.all_genes_exonic_content_block_lengths_ensemble)

    #Running SLAPenrich analysis
    PFPw<-SLAPE.analyse(EM = LUAD_CaseStudy_ugs,
                    PATH_COLLECTION = KEGG_PATH,
                    BACKGROUNDpopulation = rownames(LUAD_CaseStudy_ugs),
                    GeneLenghts = GECOBLenghts)

    #Generating a pdf file containing a heatmap of the mutual-exclusivity
    #sorted pathway alteration matrix, for an SLAPenriched pathway with
    #an exclusive coverage > 80%, and barplots with statistical scores.
    #The pdf is saved in a file with \code{Example_} as prefix in its name,
    #in the current working directory.
    SLAPE.pathvis(EM = LUAD_CaseStudy_ugs,PFP = PFPw,
        Id = PFPw$pathway_id[which(PFPw$pathway_exclusiveCoverage>80)[1]],
        prefName = 'Example_',
        PATH = './',PATH_COLLECTION = KEGG_PATH)