chr_coverage: Average signal per chromosome

In luisvalesilva/hwglabr: Collection of R functions used in the Hochwagen Lab

Description

This function allows you to calculate the average signal (or coverage) per chromosome.

Usage

chr_coverage(wiggleData, meanNorm = FALSE, orderChrs = FALSE,
  removeCen = FALSE, cenRegionSize = 50000)

Arguments

wiggleData	As a list of the 16 chr wiggle data (output of readall_tab). No default.
meanNorm	Boolean indicating whether to normalize by average genome-wide signal (calculated using function genome_average). This adds two columns to output: mean-subtracted signal and mean-divided signal. Defaults to FALSE.
orderChrs	Boolean indicating whether to order rows by chromosome length (using function order_chromosomes). Defaults to FALSE.
removeCen	Boolean indicating whether to remove regions around centromeres (using function remove_centromeres). Defaults to FALSE.
cenRegionSize	Number indicating the size (in bp) of the region to remove (centered on the centromere of each chromosome). Corresponds to argument regionSize of remove_centromeres. Defaults to 50'000 bp.

Value

A 16x2 or 16x4 R data frame:

1. chr Chromosome number

2. mean_coverage average signal

   If meanNorm=TRUE the folowing two columns are added:

3. mean_sub_coverage signal minus genome-wide average (chr_signal - genome_signal)

4. mean_div_coverage signal divided by genome-wide average (chr_signal / genome_signal)

Examples

## Not run: 
chr_coverage(WT)

chr_coverage(dot1, removeCen = TRUE, cenRegionSize = 50000)

## End(Not run)

luisvalesilva/hwglabr documentation built on May 21, 2019, 8:56 a.m.