bandStats: Find aberrations with cytoband resolution

Description Usage Arguments Value Note Author(s) See Also Examples

View source: R/chromosomeStats.R

Description

Calculate significant chromosome bands with various statistical tests

Usage

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bandStats(datalist, chromNum=1, samples=NULL, select="cli", test="fisher",
bonferroni = TRUE, enrichment = "greater")

Arguments

datalist

The CAFE datalist to be analyzed, i.e. the output of ProcessCels.

chromNum

The chromosome to be calculated. This can be "ALL" to calculate all chromosomes.

samples

A vector containing sample numbers to be analyzed

select

Signifies which type of sample selection prompt will be shown, if samples=NULL. Currently supported are "cli" for a command line interface and "gui" for a tcl/tk-based graphical user interface.

test

Signifies which statistical test to be used in the final calculation. Must be either "fisher" for an exact fisher test or "chisqr" for a chi square test.

bonferroni

If bonferroni=TRUE, will correct the p-values of the enrichment test with a bonferroni method.

enrichment

Test for over or underexpression. Can be set to "greater" or "less".

Value

A named vector containing p-values if testing a single chromosome. If chromNum="ALL", the output will be a two-column data frame, with cytoband names in the first column and p-values in the second column.

Note

Technically speaking, the Fisher's exact test is better than the chi-square test; the Fisher's exact test gives an exact p-value, whereas the chi-square test only gives an approximation. However, the Fisher's exact test can get slow for large sample sizes, and the chi-square test becomes better with increasing sample size but does not slow down as much.

Author(s)

Sander Bollen

See Also

chromosomeStats armStats

Examples

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data(CAFE_data)
bandStats(CAFE_data,chromNum=17,samples=c(1,3),test="fisher")

CAFE documentation built on Nov. 8, 2020, 7:44 p.m.