SIM (version 1.42.0)

tabulate.top.dep.features: Lists the P-values for the dependent features

Description

Lists the integrated analysis P-values for the dependent features in the analyzed regions, together with the available annotation.

Usage

tabulate.top.dep.features(input.regions = "all chrs",  adjust.method="BY",  method = c("full", "smooth", "window", "overlap"),   significance = 1,  run.name = "analysis_results")

Arguments

input.regions

vector indicating the dependent regions to be analyzed. Can be defined in four ways: 1) predefined input region: insert a predefined input region, choices are: “all chrs”, “all chrs auto”, “all arms”, “all arms auto” In the predefined regions “all arms” and “all arms auto” the arms 13p, 14p, 15p, 21p and 22p are left out, because in most studies there are no or few probes in these regions. To include them, just make your own vector of arms. 2) whole chromosome(s): insert a single chromosome or a list of chromosomes as a vector: c(1, 2, 3). 3) chromosome arms: insert a single chromosome arm or a list of chromosome arms like c("1q", "2p", "2q"). 4) subregions of a chromosome: insert a chromosome number followed by the start and end position like "chr1:1-1000000" These regions can also be combined, e.g. c("chr1:1-1000000","2q", 3). See integrated.analysis for more information.

adjust.method

Method used to adjust the P-values for multiple testing, see p.adjust. Default is “BY” recommended when copy number is used as dependent data. See SIM for more information about adjusting P-values.

method

this must be the either one of “full”, “window”, “overlap” or “smooth” but the data should generated by the same method in integrated.analysis.

significance

threshold used to select the significant dependent features. Pvalues below this threshold will be used to estimate regions.

run.name

This must be the same a given to integrated.analysis

Value

Returns a list of data.frame's for each input region. Significant P-value rich regions are returned as a data.frame. This data.frame can be used as an input for getoverlappingregions. Additionally, the results are stored in a subdirectory of run.name as txt.

Details

Output is a .txt file containing a table with sorted integrated analysis P-values of the dependent features. It includes the ann.dep columns that were read in the assemble.data function. Additionally it returns a .txt file containing the significant P-value rich regions. No P-value rich regions are returned when zscores.diag = "all".

See Also

SIM, tabulate.pvals, tabulate.top.indep.features

Examples

#first run example(assemble.data)
#and example(integrated.analysis)
#get the top dependent features sorted by p-value
table.dep <- tabulate.top.dep.features(input.regions="8q", 
		                  adjust.method="BY", 
						  method="full",
						  significance=0.05,
						  run.name="chr8q")
head(table.dep[["8q"]])