decoReport: Report of DECO analyisis

In fjcamlab/deco: Decomposing Heterogeneous Cohorts using Omic Data Profiling

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. <[e-mail]>

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)

fjcamlab/deco documentation built on Aug. 18, 2024, 4:28 a.m.