gwilcox: Calculates Wilcoxon test on sliding windows over track expression

Description

Calculates Wilcoxon test on sliding windows over the values of track expression.

Usage

gwilcox(
  expr = NULL,
  winsize1 = NULL,
  winsize2 = NULL,
  maxpval = 0.05,
  onetailed = TRUE,
  what2find = 1,
  intervals = NULL,
  iterator = NULL,
  intervals.set.out = NULL
)

Value

If 'intervals.set.out' is 'NULL' a data frame representing the intervals with an additional 'pval' column where P-value is below 'maxpval'.

Arguments

expr: track expression
winsize1: number of values in the first sliding window
winsize2: number of values in the second sliding window
maxpval: maximal P-value
onetailed: if 'TRUE', Wilcoxon test is performed one tailed, otherwise two tailed
what2find: if '-1', lows are searched. If '1', peaks are searched. If '0', both peaks and lows are searched
intervals: genomic scope for which the function is applied
iterator: track expression iterator of "fixed bin" type. If 'NULL' iterator is determined implicitly based on track expression.
intervals.set.out: intervals set name where the function result is optionally outputted

Details

This function runs a Wilcoxon test (also known as a Mann-Whitney test) over the values of track expression in the two sliding windows having an identical center. The sizes of the windows are specified by 'winsize1' and 'winsize2'. 'gwilcox' returns intervals where the smaller window tested against a larger window gives a P-value below 'maxpval'. The test can be one or two tailed.

'what2find' argument controls what should be searched: peaks, lows or both.

If 'intervals.set.out' is not 'NULL' the result is saved as an intervals set. Use this parameter if the result size exceeds the limits of the physical memory.

Examples

Run this code

# \dontshow{
options(gmax.processes = 2)
# }

gdb.init_examples()
gwilcox("dense_track", 100000, 1000,
    maxpval = 0.01,
    what2find = 1
)