binDensity

Options

Option	Description	Argument
--samplesList	File listing in one column the samples to use. If “NA” all samples are used. [default NA]	[char …]
--gipOut	GIP output directory [default gipOut]	[char]
--outName	Output name [default gipOut/sampleComparison/binDensity]	[char]
--chrs	Chromosomes to use. If “NA” it uses the same chromsomes as GIP [default NA]	[char …]
--minMAPQ	Remove bins with MAPQ < –MAPQ [default 0]	[int]
--pseudocount	Normalized mean coverage pseudocount value preventing minus infinite values in log10 transformation [default 0.1]	[double]
--highLowCovThresh	Provide two numbers. Bins with normalized coverage values > num1 or < num2 will be labeled. [default 1.5 0.5]	[double double]
--bandwidth	Smoothing bandwidth value. Provide two numbers to enforce different bandwidths on the x and y axes respectively [default 10000 0.01]	[double double]
--nbin	Number of equally spaced grid points for the density estimation. Provide two numbers to use different numbers for the x and y axes respectively [default 1000]	[int int]
--showSubset	Show a random subset of genomic bins with normalized coverage values above or below –highLowCovThresh. This random subset does not affect the density estimation [default 50000]	[int]
--debug	Dump session and quit
-h, --help	Show help message

Description

The binDensity module aims at visualizing the normalized bin sequencing coverage of multiple samples using a smoothed color density representation.

The module loads for all samples the GIP files with the bin sequencing coverage values (.covPerBin.gz files) and generates a smoothed color density scatterplot showing the genomic position (x-axis) and the log10 normalized coverage values (y-axis).

Example

From the GIP worked example folder execute

giptools binDensity

This will generate the gipOut/sampleComparison/binDensity.pdf output file. For this example the resulting plot is the following: