hicCorrectMatrix¶
Iterative correction for a HiC matrix (see Imakaev et al. 2012 Nature Methods for details). For the method to work correctly, bins with low or too high coverage need to be filtered. For this, it is recommended to first run some diagnostic plots to determine the modified zscore cut off.
It is recommended to run hicCorrectMatrix as follows:
$ hicCorrectMatrix diagnostic_plot –matrix hic_matrix o plot_file.png
Then, after revising the plot and deciding the threshold values:
 $ hicCorrectMatrix correct –matrix hic_matrix
 –filterThreshold <lower threshold> <upper threshold> o corrected_matrix
usage: hicCorrectMatrix [h] [version] [verbose] ...
Named Arguments¶
–version  show program’s version number and exit 
–verbose  Print processing status Default: False 
commands¶
Possible choices: correct, diagnostic_plot

Subcommands:¶
correct¶
Run the iterative correction.
hicCorrectMatrix correct matrix hic_matrix.h5 filterThreshold 1.2 5out corrected_matrix.h5
Named Arguments¶
–matrix, m  HiC matrix. 
–iterNum, n  number of iterations Default: 500 
–outFileName, o  
File name to save the resulting matrix. The output is a .h5 file.  
–filterThreshold, t  
Bins of low coverage or large coverage need to be removed. Usually they do not contain valid HiC data of represent regions that accumulate reads. Use hicCorrectMatrix diagnostic_plot to identify the modified zvalue thresholds. A lower and upper threshold are required separated by space. Eg. –filterThreshold 1.5 5  
–inflationCutoff  
Value corresponding to the maximum number of times a bin can be scaled up during the iterative correction. For example, a inflation Cutoff of 3 will filter out all bins that were expanded 3 times or more during the iterative correction.  
–transCutoff, transcut  
Clip high counts in the top transcut trans regions (i.e. between chromosomes). A usual value is 0.05  
–sequencedCountCutoff  
Each bin receives a value indicating the fraction that is covered by reads. A cutoff of 0.5 will discard all those bins that have less than half of the bin covered.  
–chromosomes  List of chromosomes to be included in the iterative correction. The order of the given chromosomes will be then kept for the resulting corrected matrix 
–skipDiagonal, s  
If set, diagonal counts are not included Default: False  
–perchr  Normalize each chromosome separately Default: False 
–verbose  Print processing status Default: False 
–version  show program’s version number and exit 
diagnostic_plot¶
Plots a histogram of the coverage per bin together with the modified zscore based on the median absolute deviation method (see Boris Iglewicz and David Hoaglin 1993, Volume 16: How to Detect and Handle Outliers The ASQC Basic References in Quality Control: Statistical Techniques, Edward F. Mykytka, Ph.D., Editor.
hicCorrectMatrix diagnostic_plot matrix hic_matrix.h5 o file.png
Named Arguments¶
–matrix, m  HiC matrix. 
–plotName, o  File name to save the diagnostic plot. 
–chromosomes  List of chromosomes to be included in the iterative correction. The order of the given chromosomes will be then kept for the resulting corrected matrix 
–xMax  Max value for the xaxis in counts per bin 
–perchr  Compute histogram per chromosome. For samples from cells with uneven number of chromosomes and/or translocations it is advisable to check the histograms per chromosome to find the most conservative filterThreshold. Default: False 