decoReport {deco} | R Documentation

## Report of DECO analyisis

### Description

This report includes a PDF file with several different representations from the analysis. Additionally, a text file (tabulated-delimited) including featureTable slot from a deco R object and a text file with h statistics per feature and subclass found were both generated. They will be created inside current working directory.

### Usage

    decoReport(deco, sub, id = NA, pdf.file = "decoReport.pdf",
                     info.sample = NA, info.feature = NA,
                     cex.samples = 1.2, cex.legend = 0.9,
                     cex.names = 0.8, print.annot = FALSE)

### Arguments

`deco` | a "deco" R object generated by 'decoNSCA' R function.
`sub` | a R object generated by 'decoRDA' R function.
`id` | character vector indicating what original IDs from input data should be highlighted and plot in 'Profile' section. If all IDs found have to be plot, input all corresponding IDs here.
`pdf.file` | path or name of pdf where report should be generated.
`info.sample` | a factor or data.frame with relevant information of samples to be plot on 'Heatmap'.
`info.feature` | a factor or data.frame with relevant information of genes or features to be plot on 'Heatmap'.
`cex.samples` | numerical value giving the amount of magnification of sample related information, i.e. sample points in 'Profile' plots.
`cex.legend` | numerical value giving the amount of magnification of legend.
`cex.names` | numerical value giving the amount of magnification to gene names or sample names.
`print.annot` | logical indicating if annotation (gene SYMBOL) should be printed instead original IDs. This option needs previous annotation within 'decoRDA' function or late annotation binding information to @featureTable slot of 'deco' R object.

### Value

Returns a 'pdf' file including relevant information about all DECO algorithm analysis.

### Author(s)

Francisco Jose Campos Laborie. <fjcamlab@usal.es>

### See Also

Vignette of R package explains all different plots included within the pdf.

`decoRDA`, `decoNSCA`

### Examples

    # Phenotypical data from TCGA RNAseq samples.
    data(ALCLdata)
    head(colData(ALCL))

    #####################################################
    # PDF report with gene-sample patterns or subgroups #
    #####################################################
    ## Generate PDF report with relevant information and several plots.
    # It will also generate a txt (tab-delimitated) table including featureTable.
    # Both objects will be saved in your working directory if any path is given in PDF name.

    ## Binary example (ALK+ vs ALK-)
    # decoReport(deco.results.ma, sub.ma.3r.1K,
    #            pdf.file = "report_example_microarray_binary.pdf",
    #            info.sample = as.data.frame(colData(ALCL))[,8:10],
    #            cex.names = 0.3, print.annot = TRUE)

    ## Unsupervised example (no classes)
    # decoReport(deco.results.ma.uns, sub.ma.3r.1K.uns,
    #            pdf.file = "report_example_microarray_unsupervised.pdf",
    #            info.sample = as.data.frame(colData(ALCL))[,8:10],
    #            cex.names = 0.3, print.annot = TRUE)

    ## Multiclass example (ALK+ vs PTCL vs ALK-(noPTCL))
    # decoReport(deco.results.ma.multi, sub.ma.3r.1K.multi,
    #            pdf.file = "report_example_microarray_multi.pdf",
    #            info.sample = as.data.frame(colData(ALCL))[,8:10],
    #            cex.names = 0.3, print.annot = TRUE)

[Package deco version 1.8.0 Index]