# chicQualityControl¶

Computes the sparsity of each viewpoint to determine the quality. A viewpoint is considered to be of bad quality if it is too sparse i.e. if there are too many locations with no interactions recorded.

This script creates three output files: a plot with the sparsity distribution per matrix, a plot with the sparsity distribution as histograms and a filtered reference points file.

An example usage is:

\$ chicQualityControl -m matrix1.h5 matrix2.h5 -rp referencePointsFile.bed –range 20000 40000 –sparsity 0.01 -o referencePointFile_QC_passed.bed

usage: chicQualityControl --matrices MATRICES [MATRICES ...] --referencePoints
REFERENCEPOINTS --sparsity SPARSITY
[--outFileName OUTFILENAME]
[--outFileNameHistogram OUTFILENAMEHISTOGRAM]
[--outFileNameSparsity OUTFILENAMESPARSITY]
[--dpi DPI] [--help] [--version]


## Required arguments¶

--matrices, -m

The input matrices to apply the QC on.

--referencePoints, -rp

Bed file contains all reference points which are checked for a sufficient number of interactions.

--sparsity, -s

Viewpoints with a sparsity less than the value given are considered of bad quality. If multiple matrices are given, the viewpoint is removed as soon as it is of bad quality in at least one matrix.

## Optional arguments¶

--outFileName, -o

The output file name of the passed reference points. Used as prefix for the plots as well.

Default: “new_referencepoints.bed”

--outFileNameHistogram, -oh

The output file for the histogram plot.

Default: “histogram.png”

--outFileNameSparsity, -os

The output file for the sparsity distribution plot.

Default: “sparsity.png”

Default: 4

--fixateRange, -fs

Fixate score of background model starting at distance x. E.g. all values greater than 500kb are set to the value of the 500kb bin.

Default: 500000

--dpi

Optional parameter: Resolution for the image if theoutput is a raster graphics image (e.g png, jpg)

Default: 300

--version

show program’s version number and exit