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hicCompartmentalization (version 3.7.2+galaxy0)

Matricies to compute on:

Eigenvector file:

A PCA vector as a bedgraph file with no header. In case of several matrices with different conditions, ie. control treatment, the PCA of control can be used. Note that only one PCA can be provided.

Quantile:

The number of to be used quantiles.

Outliers:

The number of outliers to be removed.

Offset values:

Image output format:

Output matrix?:

Comparmentalization

hicCompartmentalization rearranges the average interaction frequencies using the first PC values to represent the global compartmentalization signal. To our knowledge this has been first introduced and implemented by Wibke Schwarzer et al. 2017 (Nature. 2017 Nov 2; 551(7678): 51–56)

For more information about HiCExplorer please consider our documentation on readthedocs.io.