tabulate.pvals: Sums significant P-values for the analyzed regions

Description Usage Arguments Value Author(s) See Also Examples

View source: R/tabulate.pvals.R

Description

Generates a data.frame with the significance of P-values in the analyzed regions, dividing them into bins.

Usage

1
2
3
4
5
6
7
8
tabulate.pvals(input.regions = "all chrs", 
               adjust.method = "BY", 
               bins = c(0.001, 0.005, 0.01, 0.025, 0.05, 0.075, 0.1, 0.2, 1), 
               significance.idx = 8, 
               order.by, 
               decreasing = TRUE, 
               method = c("full", "smooth", "window", "overlap"),
              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.

bins

vector of significance thresholds. This function will calculate the number of features having a P-value lower than the bin.

significance.idx

Index of “bins” to use when computing the percentage of significant P-values. Defaults to 8 (i.e. the first entry in “bins”), in this case 0.20.

order.by

Column used for sorting the table. Defaults to "%" (i.e. the percentage of significant p-values).

decreasing

Direction used for sorting. Defaults to TRUE (i.e. highest values on top).

method

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

run.name

This must be the same a given to integrated.analysis

Value

Returns a data.frame. Each row corresponds to a chromosome and has as many entries as entries in bins, plus 1. Each entry contains the number of P-values that is smaller or equal to the corresponding entry in bins.

The last entry holds the percentage of P-values that is smaller than or equal to the bin identified by significance.idx.

Author(s)

Marten Boetzer, Melle Sieswerda, Renee X. de Menezes [email protected]

See Also

SIM, tabulate.top.dep.features, tabulate.top.indep.features

Examples

1
2
3
4
5
6
#first run example(assemble.data)
#and example(integrated.analysis)
tabulate.pvals(input.regions="8q",
		       adjust.method="BY", 
			   bins=c(0.001,0.005,0.01,0.025,0.05,0.075,0.10,0.20,1.0),			   			    
			   run.name="chr8q") 

Bioconductor-mirror/SIM documentation built on June 1, 2017, 1:15 a.m.